diff --git a/setup.py b/setup.py
index c2cde5f..b4fd371 100644
--- a/setup.py
+++ b/setup.py
@@ -8,7 +8,7 @@
     readme = readme_file.read()
 
 requirements = ["pandas > 1.2.0", "pandas< 2.0.0",
-                "scipy>=1.8.0", "scipy<2.0.0"]
+                "scipy>=1.8.0", "scipy<2.0.0", "shapely"]
 test_requirements = ['pytest>=3', ]
 
 setup(
diff --git a/study_lyte/adjustments.py b/study_lyte/adjustments.py
index 7ac014a..a8949c3 100644
--- a/study_lyte/adjustments.py
+++ b/study_lyte/adjustments.py
@@ -2,7 +2,7 @@
 import pandas as pd
 from scipy.signal import lfilter
 
-def get_points_from_fraction(n_samples, fraction):
+def get_points_from_fraction(n_samples, fraction, maximum=None):
     """
     Return the nearest whole int from a fraction of the
     number of samples. Never returns 0.
@@ -10,6 +10,11 @@ def get_points_from_fraction(n_samples, fraction):
     idx = int(fraction * n_samples) or 1
     if idx == n_samples:
         idx = n_samples - 1
+
+    if maximum is not None:
+        if idx > maximum:
+            idx = maximum
+
     return idx
 
 
@@ -45,6 +50,25 @@ def get_neutral_bias_at_border(series: pd.Series, fractional_basis: float = 0.00
     bias_adj = series - bias
     return bias_adj
 
+def get_neutral_bias_at_index(series: pd.Series, index, fractional_basis: float = 0.005):
+    """
+    Bias adjust the series data by using the XX % of the data centered on an provided index
+
+    Args:
+        series: pandas series of data with a known bias
+        fractional_basis: Fraction of data to use to estimate the bias on start
+    Returns:
+        bias_adj: bias adjusted data to near zero
+    """
+    n = get_points_from_fraction(len(series), fractional_basis)
+    start = index-n
+    start = start if start > 0 else 0
+    stop = index + n
+    stop = stop if stop < len(series) else len(series)-1
+
+    bias = series.values[start:stop].mean()
+    bias_adj = series - bias
+    return bias_adj
 
 def get_normalized_at_border(series: pd.Series, fractional_basis: float = 0.01, direction='forward'):
     """
@@ -155,23 +179,40 @@ def apply_calibration(series, coefficients, minimum=None, maximum=None):
     return result
 
 
-def aggregate_by_depth(df, new_depth, df_depth_col='depth', agg_method='mean'):
+def aggregate_by_depth(df, new_depth=None, resolution=None, df_depth_col='depth', agg_method='mean'):
     """
     Aggregate the dataframe by the new depth using whatever method
     provided. Data in the new depth is considered to be the bottom of
     the aggregation e.g. 10, 20 == 0-10, 11-20 etc
     Depth data must be monotonic.
     new_depth data much be coarser than current depth data
+
+    Args:
+        df: Dataframe containing at least depth as a columne
+        new_depth: Optional array of depth positions to aggregate to (useful for arbitrary delineations e.g. hand hardness)
+        resolution: Aggregate to a resolution in centimeter. Optional
+        df_depth_col: Column name for depth
+        agg_method: Method to aggregate
+
+
     """
+    # Determine new depth data
+    if new_depth is None:
+        resolution = -1 * abs(resolution)
+        new_depth = np.arange(resolution, df[df_depth_col].min() + resolution, resolution)
+
+    # Determine datum type
     if new_depth[-1] < 0:
         surface_datum = True
     else:
         surface_datum = False
+
     if df.index.name is not None:
         df = df.reset_index()
     dcol = df_depth_col
     cols = [c for c in df.columns if c not in [dcol, 'time']]
     new = []
+
     # is the user request specific aggregation by column
     agg_col_specific = True if type(agg_method) == dict else False
 
@@ -195,6 +236,7 @@ def aggregate_by_depth(df, new_depth, df_depth_col='depth', agg_method='mean'):
                 ind = ind & (df[dcol] >= d1)
             else:
                 ind = ind & (df[dcol] > d1)
+
         if agg_col_specific:
             for z,c in enumerate(cols):
                 nr = getattr(df[c][ind], agg_method[c])()
diff --git a/study_lyte/depth.py b/study_lyte/depth.py
index e3b6c24..0d3c373 100644
--- a/study_lyte/depth.py
+++ b/study_lyte/depth.py
@@ -123,13 +123,6 @@ def get_constrained_baro_depth(baro_depth, start, stop, method='nanmedian'):
     constrained = result.set_index('time')
     #assume_no_upward_motion(result[baro])
     constrained = constrained - constrained.iloc[0]
-
-    # from .plotting import plot_constrained_baro
-    # pos = get_depth_from_acceleration(df).mul(100)
-    # pos = pos.reset_index()
-    # plot_constrained_baro(df, result, const, pos, top, bottom, start, stop,
-    #                       baro=baro, acc_axis=acc_axis)
-
     return constrained
 
 
diff --git a/study_lyte/detect.py b/study_lyte/detect.py
index cc6f442..7b04b5b 100644
--- a/study_lyte/detect.py
+++ b/study_lyte/detect.py
@@ -1,9 +1,16 @@
 import numpy as np
 from scipy.signal import find_peaks, argrelextrema
 
-from .adjustments import get_neutral_bias_at_border, get_normalized_at_border, get_points_from_fraction
+from .adjustments import (get_neutral_bias_at_border, get_normalized_at_border, get_points_from_fraction, get_neutral_bias_at_index,zfilter)
 from .decorators import directional
 
+def find_nearest_value_index(search_value, series):
+    """
+    Given an array and a value, this function finds the index of the
+    value closest to the search value
+    """
+    idx = np.abs(search_value - series).argmin()
+    return idx
 
 def first_peak(arr, default_index=1, **find_peak_kwargs):
     """
@@ -95,14 +102,16 @@ def get_signal_event(signal_series, threshold=0.001, search_direction='forward',
 
     # If no results are found, return the first index the series
     if len(ind) == 0:
-        event_idx = 0
+        event_idx = None
     else:
         # Return the first value matching the conditions
         event_idx = ind[-1]
 
     # Invert the index
-    if 'backward' in search_direction:
+    if 'backward' in search_direction and event_idx is not None:
         event_idx = len(arr) - 1 - event_idx
+        # if event_idx == 0:
+        #     event_idx = None
 
     return event_idx
 
@@ -126,10 +135,12 @@ def get_acceleration_start(acceleration, threshold=-0.01, max_threshold=0.02):
     acceleration_start = get_signal_event(accel_neutral[0:max_ind+1], threshold=threshold, max_threshold=max_threshold,
                                           n_points=n_points,
                                           search_direction='forward')
+    if acceleration_start is None:
+        acceleration_start = 0
     return acceleration_start
 
 
-def get_acceleration_stop(acceleration, threshold=-0.05, max_threshold=0.05):
+def get_acceleration_stop(acceleration, threshold=-0.2, max_threshold=0.1):
     """
     Returns the index of the last value that has a relative change greater than the
     threshold of absolute normalized signal
@@ -141,9 +152,6 @@ def get_acceleration_stop(acceleration, threshold=-0.05, max_threshold=0.05):
         acceleration_start: Integer of index in array of the first value meeting the criteria
     """
     acceleration = acceleration.values
-    n = get_points_from_fraction(len(acceleration), 0.005)
-    if n > 40:
-        n = 20
 
     min_idx = np.argwhere(acceleration == acceleration.min())[0][0]
     max_idx = np.argwhere(acceleration == acceleration.max())[0][0]
@@ -156,11 +164,16 @@ def get_acceleration_stop(acceleration, threshold=-0.05, max_threshold=0.05):
         # Use the farthest deceleration
         search_start = min_idx
 
+    n = get_points_from_fraction(len(acceleration[search_start:]), 0.05, maximum=1000)
     acceleration_stop = get_signal_event(acceleration[search_start:], threshold=threshold,
                                          max_threshold=max_threshold,
                                          n_points=n,
                                          search_direction='backward')
-    acceleration_stop = acceleration_stop + search_start
+
+    if acceleration_stop is None:
+        acceleration_stop = len(acceleration) - 1
+    else:
+        acceleration_stop = acceleration_stop + search_start
     return acceleration_stop
 
 
@@ -209,7 +222,8 @@ def get_nir_stop(active, fractional_basis=0.05, max_threshold=0.008, threshold=-
     n_points = get_points_from_fraction(len(data), fractional_basis)
     stop = get_signal_event(data, search_direction='backward', threshold=threshold,
                             max_threshold=max_threshold, n_points=n_points)
-    stop += ind
+    if stop is not None:
+        stop += ind
 
     return stop
 
@@ -218,10 +232,41 @@ def get_sensor_start(signal, fractional_basis=0.05, max_threshold=0.05, threshol
     """
     Before entering the snow we don't see much dynamic signal. This detects the first change in the signal
     """
-    ind = np.where(signal == signal.max())[0][0]
+    ind = np.where(signal == signal.min())[0][0]
     n_points = get_points_from_fraction(len(signal), 0.01)
     data = signal[:ind]
     norm_signal = get_normalized_at_border(data, fractional_basis=fractional_basis, direction='forward') - 1
     first_change = get_signal_event(norm_signal, search_direction='forward', threshold=threshold,
                             max_threshold=max_threshold, n_points=n_points)
-    return first_change
\ No newline at end of file
+    return first_change
+
+
+def get_ground_strike(signal, stop_idx):
+    """
+    The probe hits ground somtimes before we detect stop.
+    """
+    buffer = get_points_from_fraction(len(signal), 0.05)
+    start = stop_idx - buffer
+    start = start if start > 0 else 0
+    end = stop_idx + buffer
+    end = end if end < len(signal) else len(signal)-1
+    rel_stop = stop_idx - start
+
+    sig_arr = signal[start:end]
+    norm1 = get_neutral_bias_at_index(sig_arr, rel_stop + buffer)
+
+    # norm1 = get_neutral_bias_at_border(signal[start:end], 0.1, 'backward')
+    diff = zfilter(norm1.diff(), 0.001)    # Large change in signal
+    impact = get_signal_event(diff, threshold=-1000, max_threshold=-70, n_points=1, search_direction='forward')
+
+    # Large chunk of data that's the same near the stop
+    n_points = get_points_from_fraction(len(norm1), 0.1)
+    long_press = get_signal_event(norm1, threshold=-150, max_threshold=150, n_points=n_points, search_direction='backward')
+    tol = get_points_from_fraction(len(norm1), 0.2)
+
+    ground = None
+    if impact is not None and long_press is not None:
+        if (long_press-tol) <= impact <= (long_press+tol):
+            ground = impact + start
+
+    return ground
\ No newline at end of file
diff --git a/study_lyte/io.py b/study_lyte/io.py
index 8c14590..4b51a27 100644
--- a/study_lyte/io.py
+++ b/study_lyte/io.py
@@ -2,19 +2,9 @@
 import pandas as pd
 import numpy as np
 
+def find_metadata(f:str) -> [int, dict]:
+    """Read just the metadata from the probe files"""
 
-def read_csv(f: str) -> Tuple[pd.DataFrame, dict]:
-    """
-    Reads any Lyte probe CSV and returns a dataframe
-    and metadata dictionary from the header
-
-    Args:
-        f: Path to csv, or file buffer
-    Returns:
-        tuple:
-            **df**: pandas Dataframe
-            **header**: dictionary containing header info
-    """
     # Collect the header
     metadata = {}
 
@@ -32,17 +22,35 @@ def read_csv(f: str) -> Tuple[pd.DataFrame, dict]:
             else:
                 header_position = i
                 break
+    return header_position, metadata
 
-        df = pd.read_csv(f, header=header_position)
-        # Drop any columns written with the plain index
-        df.drop(df.filter(regex="Unname"), axis=1, inplace=True)
+def read_data(f:str, metadata:dict, header_position:int) -> Tuple[pd.DataFrame, dict]:
+    """Read just the csv to enable parsing metadata and header position separately"""
+    df = pd.read_csv(f, header=header_position)
+    # Drop any columns written with the plain index
+    df.drop(df.filter(regex="Unname"), axis=1, inplace=True)
 
-        if 'time' not in df and 'SAMPLE RATE' in metadata:
-            sr = int(metadata['SAMPLE RATE'])
-            n = len(df)
-            df['time'] = np.linspace(0, n/sr, n)
+    if 'time' not in df and 'SAMPLE RATE' in metadata:
+        sr = int(metadata['SAMPLE RATE'])
+        n = len(df)
+        df['time'] = np.linspace(0, n/sr, n)
+    return df, metadata
 
-        return df, metadata
+def read_csv(f: str) -> Tuple[pd.DataFrame, dict]:
+    """
+    Reads any Lyte probe CSV and returns a dataframe
+    and metadata dictionary from the header
+
+    Args:
+        f: Path to csv, or file buffer
+    Returns:
+        tuple:
+            **df**: pandas Dataframe
+            **header**: dictionary containing header info
+    """
+    header_position, metadata = find_metadata(f)
+    df, metadata = read_data(f, metadata, header_position)
+    return df, metadata
 
 
 def write_csv(df: pd.DataFrame, meta: dict, f: str) -> None:
diff --git a/study_lyte/plotting.py b/study_lyte/plotting.py
index 7633b7a..307462c 100644
--- a/study_lyte/plotting.py
+++ b/study_lyte/plotting.py
@@ -108,4 +108,19 @@ def plot_fused_depth(acc_depth, baro_depth, avg, scaled_baro=None, error=None):
         ax = plot_ts(scaled_baro, ax=ax, data_label='Scaled Baro', show=False)
 
     ax.legend()
-    plt.show()
\ No newline at end of file
+    plt.show()
+
+
+
+def plot_ground_strike(signal, search_start, stop_idx, impact, long_press, ground):
+    events = [('stop', stop_idx)]
+    if long_press is not None:
+        events.append(('long_press', long_press + search_start))
+    if impact is not None:
+        events.append(('impact', impact + search_start))
+    if ground is not None:
+        events.append(('ground', ground))
+    ax = plot_ts(signal, events=events,show=False)
+    ax.legend()
+    plt.show()
+
diff --git a/study_lyte/profile.py b/study_lyte/profile.py
index d704b5d..d4076f0 100644
--- a/study_lyte/profile.py
+++ b/study_lyte/profile.py
@@ -4,10 +4,11 @@
 from pathlib import Path
 from types import SimpleNamespace
 import numpy as np
+from shapely.geometry import Point
 
-from . io import read_csv
+from . io import read_data, find_metadata
 from .adjustments import get_neutral_bias_at_border, remove_ambient, apply_calibration, get_points_from_fraction, zfilter
-from .detect import get_acceleration_start, get_acceleration_stop, get_nir_surface, get_nir_stop, get_sensor_start
+from .detect import get_acceleration_start, get_acceleration_stop, get_nir_surface, get_nir_stop, get_sensor_start, get_ground_strike
 from .depth import AccelerometerDepth, BarometerDepth
 from .logging import setup_log
 import logging
@@ -26,7 +27,6 @@ class Sensor(Enum):
     UNAVAILABLE = -1
 
 
-
 class LyteProfileV6:
         def __init__(self, filename, surface_detection_offset=4.5, calibration=None, depth_method='fused', tip_diameter_mm=5):
             """
@@ -49,6 +49,8 @@ def __init__(self, filename, surface_detection_offset=4.5, calibration=None, dep
             self._meta = None
             self._accelerometer = None
             self._barometer = None
+            self._point = None
+            self.header_position = None
 
             self._depth = None # Final depth series used for analysis
             self._acceleration = None # No gravity acceleration
@@ -72,6 +74,7 @@ def __init__(self, filename, surface_detection_offset=4.5, calibration=None, dep
             self._stop = None
             self._surface = None
             self._error = None
+            self._ground = None
 
         @staticmethod
         def process_df(df):
@@ -103,7 +106,8 @@ def raw(self):
             Pandas dataframe hold the data exactly as it read in.
             """
             if self._raw is None:
-                self._raw, self._meta = read_csv(str(self.filename))
+                metadata = self.metadata
+                self._raw, self._meta = read_data(str(self.filename), metadata, self.header_position)
                 self._raw = self.process_df(self.raw)
 
             return self._raw
@@ -113,22 +117,21 @@ def metadata(self):
             """
             Returns a dictionary of all data held in the header portion of the csv
             """
-            if self._raw is None:
-                self._raw, self._meta = read_csv(str(self.filename))
-                self._raw = self.process_df(self.raw)
+            if self._meta is None:
+                self.header_position, self._meta = find_metadata(str(self.filename))
 
-            # Manage misc naming of the acceleration range
-            if 'ACC. Range' not in self._meta.keys():
-                if "ACCRANGE" in self._meta.keys():
-                    self._meta['ACC. Range'] = float(self._meta['ACCRANGE'])
-                else:
-                    self._meta['ACC. Range'] = 2
+                # Manage misc naming of the acceleration range
+                if 'ACC. Range' not in self._meta.keys():
+                    if "ACCRANGE" in self._meta.keys():
+                        self._meta['ACC. Range'] = float(self._meta['ACCRANGE'])
+                    else:
+                        self._meta['ACC. Range'] = 2
 
-            else:
-                self._meta['ACC. Range'] = float(self._meta['ACC. Range'])
+                else:
+                    self._meta['ACC. Range'] = float(self._meta['ACC. Range'])
 
-            if 'ZPFO' in self._meta.keys():
-                self._meta['ZPFO'] = int(self._meta['ZPFO'])
+                if 'ZPFO' in self._meta.keys():
+                    self._meta['ZPFO'] = int(self._meta['ZPFO'])
 
             return self._meta
 
@@ -167,8 +170,10 @@ def nir(self):
             Retrieve the Active NIR sensor with ambient NIR removed
             """
             if self._nir is None:
-                self._nir = pd.DataFrame({'nir': self.raw['nir'].values, 'depth': self.depth.values})
-                self._nir = self._nir.iloc[self.surface.nir.index:self.stop.index].reset_index()
+                self._nir = self.raw[["Sensor2","Sensor3", "nir"]]
+                self._nir['depth'] = self.depth.values
+                end = self.stop.index if self.ground.index is None else self.ground.index
+                self._nir = self._nir.iloc[self.surface.nir.index:end].reset_index()
                 self._nir = self._nir.drop(columns='index')
                 self._nir['depth'] = self._nir['depth'] - self._nir['depth'].iloc[0]
             return self._nir
@@ -186,7 +191,9 @@ def force(self):
                     force = self.raw['Sensor1'].values
 
                 self._force = pd.DataFrame({'force': force, 'depth': self.depth.values})
-                self._force = self._force.iloc[self.surface.force.index:self.stop.index].reset_index()
+                # prefer a ground index if available
+                end = self.stop.index if self.ground.index is None else self.ground.index
+                self._force = self._force.iloc[self.surface.force.index:end].reset_index()
                 self._force = self._force.drop(columns='index')
                 if not self._force.empty:
                     self._force['depth'] = self._force['depth'] - self._force['depth'].iloc[0]
@@ -232,9 +239,6 @@ def barometer(self):
                 else:
                     idx = self.start.index
                 self._barometer = BarometerDepth(baro, idx, self.stop.index)
-            # from .plotting import plot_ts
-            # ax = plot_ts(self.accelerometer.depth.values, events=[('start', idx)], show=False)
-            # plot_ts(self._barometer.depth.values, events=[('start', idx)], ax=ax)
 
             return self._barometer
 
@@ -287,7 +291,11 @@ def stop(self):
                     idx = get_acceleration_stop(backward_accel)
                 else:
                     idx = get_nir_stop(self.raw['Sensor3'])
-                self._stop = Event(name='stop', index=idx, depth=None, time=self.raw['time'].iloc[idx])
+                if idx is not None:
+                    self._stop = Event(name='stop', index=idx, depth=None, time=self.raw['time'].iloc[idx])
+                else:
+                    self._stop = Event(name='stop', index=0, depth=None, time=self.raw['time'].iloc[0])
+
             return self._stop
 
         @property
@@ -307,15 +315,17 @@ def surface(self):
                 force_surface_depth = depth + self.surface_detection_offset
                 f_idx = abs(self.depth - force_surface_depth).argmin()
                 # Retrieve force estimated start
-                f_start = get_sensor_start(self.raw['Sensor1'], max_threshold=0.3, threshold=-0.3)
+                f_start = get_sensor_start(self.raw['Sensor1'], max_threshold=0.02, threshold=-0.02)
+                f_start = f_start or f_idx
+
                 # If the force start is before the NIR start then adjust
                 if f_start < self.start.index:
-                    LOG.info('Choosing motion start over force start...')
+                    LOG.info(f'Choosing motion start ({self.start.index}) over force start ({f_start})...')
                     f_idx = self.start.index
                     force_surface_depth = self.depth.iloc[f_idx]
 
                 elif f_start < f_idx:
-                    LOG.info('Choosing force start point over nir...')
+                    LOG.info(f'Choosing force start ({f_start}) over nir derived ({f_idx})...')
                     f_idx = f_start
                     force_surface_depth = self.depth.iloc[f_idx]
 
@@ -328,6 +338,17 @@ def surface(self):
                     self._start.name = 'start'
 
             return self._surface
+        @property
+        def ground(self):
+            """Event for ground detection"""
+            if self._ground is None:
+                ground = get_ground_strike(self.raw['Sensor1'], self.stop.index)
+                if ground is not None:
+                    self._ground = Event(name='ground', index=ground, depth=self.depth.iloc[ground], time=self.raw['time'].iloc[ground])
+                else:
+                    self._ground = Event(name='ground', index=None, depth=None, time=None)
+
+            return self._ground
 
         @property
         def error(self):
@@ -394,7 +415,7 @@ def events(self):
             """
             Return all the common events recorded
             """
-            return [self.start, self.stop, self.surface.nir, self.surface.force, self.error]
+            return [self.start, self.stop, self.surface.nir, self.surface.force, self.ground, self.error]
 
         @staticmethod
         def get_motion_name(columns):
@@ -419,6 +440,16 @@ def get_acceleration_columns(columns):
                 return candidates
             else:
                 return Sensor.UNAVAILABLE
+        @property
+        def point(self):
+            """Return shapely geometry point of the measurement location in EPSG 4326"""
+            if self._point is None:
+                if all([k in self.metadata.keys() for k in ['Latitude', 'Longitude']]):
+                    self._point = Point(float(self.metadata['Longitude']), float(self.metadata['Latitude']))
+                else:
+                    self._point = Sensor.UNAVAILABLE
+
+            return self._point
 
         def report_card(self):
             """
@@ -436,8 +467,9 @@ def report_card(self):
             profile_string += msg.format('Resolution', f'{self.resolution:0.1f} pts/cm')
             profile_string += msg.format('Total Travel', f'{self.distance_traveled:0.1f} cm')
             profile_string += msg.format('Snow Depth', f'{self.distance_through_snow:0.1f} cm')
-            profile_string += msg.format('Error Detected:', f'@ {self.error.time:0.1f} s' if self.error.time is not None else 'None')
-            profile_string += msg.format('Upward Motion?:', "True" if self.has_upward_motion else "False")
+            profile_string += msg.format('Ground Strike:', 'True' if self.ground.time is not None else 'False')
+            profile_string += msg.format('Upward Motion:', "True" if self.has_upward_motion else "False")
+            profile_string += msg.format('Errors:', f'@ {self.error.time:0.1f} s' if self.error.time is not None else 'None')
 
             profile_string += '-' * (len(header)-2) + '\n'
             return profile_string
@@ -470,12 +502,13 @@ def fuse_depths(cls, acc_depth, baro_depth, error=None):
             # The deeper we go the more the baro constrains
             baro_bottom = baro_depth.min()
             acc_bottom = acc_depth.min()
-            scale = abs(acc_bottom / 100)
             avg_bottom = avg.min()
 
             # Scale total
-            delta = (acc_bottom * (5 - scale) + baro_bottom * scale) / 5
-            avg = (avg / avg_bottom) * delta
+            sensor_diff = abs(acc_bottom) - abs(baro_bottom)
+            delta = 0.572 * abs(acc_bottom) + 0.308 * abs(baro_bottom) + 0.264 * sensor_diff + 8.916
+            # delta = (acc_bottom * (5 - scale) + baro_bottom * scale) / 5
+            avg = (avg / avg_bottom) * -1*delta
             return avg
 
 
diff --git a/study_lyte/relationships.py b/study_lyte/relationships.py
new file mode 100644
index 0000000..72dc571
--- /dev/null
+++ b/study_lyte/relationships.py
@@ -0,0 +1,204 @@
+import numpy as np
+from string import ascii_uppercase
+
+class LinearRegression:
+    """
+    Class for managing simple linear regressions
+    """
+    def __init__(self, coefficients=None, predicted_name=None, coefficient_names=None):
+        """
+        Args:
+            coefficients: If a regression has already be formed then instantiate from there.
+            predicted_name: Name to use in various strings for outputting name.
+            coefficient_names: Names of the coefficients to use in various strings.
+
+        """
+        self._coefficients = coefficients
+        self._name = predicted_name
+        self._coefficient_names = coefficient_names
+        # String holder for a plain text equation and one renderable for latex
+        self._equation = None
+        self._rendered_equation = None
+        self._n_points = None
+
+    @property
+    def n_points(self):
+        """Number of records used for the regression, may be 'Unknown' in the event that the
+         relationship is pre-computed
+         """
+        if self._n_points is None:
+            self._n_points = 'Unknown'
+        return self._n_points
+
+    @property
+    def coefficients(self):
+        """Resulting coefficients from the regression"""
+        if self._coefficients is None:
+            self._coefficients = []
+        return self._coefficients
+
+    @property
+    def coefficient_names(self):
+        """name to use in strings outputting information"""
+        if self._coefficient_names is None:
+            # Use made up variables.
+            if self.coefficients:
+                self._coefficient_names = [f"{ascii_uppercase[-1*(i+1)]}" for i,c in enumerate(self.coefficients[0:-1])]
+
+        if len(self._coefficient_names) != len(self.coefficients):
+            self._coefficient_names.append('')
+
+        return self._coefficient_names
+
+    @property
+    def name(self):
+        """name to use in strings outputting information"""
+        if self._name is None:
+            self._name = 'data'
+        return self._name
+
+    @property
+    def equation(self):
+        """Useful string representation of resulting equation"""
+        if self._equation is None:
+            self._equation = self.get_equation_string()
+        return self._equation
+
+    @property
+    def rendered_equation(self):
+        """Useful string representation"""
+        if self._rendered_equation is None:
+            self._rendered_equation = self.get_equation_string(rendered=True)
+        return self._rendered_equation
+
+    def regress(self, input_df, output_series):
+        """
+        Take a pandas dataframe and form a regression against the output series
+        data
+        Args:
+            input_df: Pandas Dataframe containing inputs to the regression. Column names are used in equation.
+            if columns names are written in latex, they can be rendered in rendered equation for matplotlib
+            output_series: Data to regress against
+        """
+        columns = list(input_df.columns)
+        # Set string columns names anytime we regress. Clear our equation string
+        self._coefficient_names = columns
+        self._equation = None
+        self._rendered_equation = None
+        self._n_points = len(input_df.index)
+        a_matrix = np.vstack([input_df[c] for c in columns] + [np.ones(len(input_df.index))]).T
+        # Filter out rows with Nans
+        final = []
+        final_output = []
+        for i in range(a_matrix.shape[0]):
+            if not np.any(np.isnan(a_matrix[i])) and not np.isnan(output_series[i]):
+                final.append(a_matrix[i])
+                final_output.append(output_series[i])
+        a_matrix = np.array(final)
+        output_series = np.array(final_output)
+
+        self._coefficients = list(np.linalg.lstsq(a_matrix, output_series, rcond=None)[0])
+
+    def predict(self, input_df):
+        """
+        Use the regression to predict data
+        Args:
+            input_df: Pandas Dataframe containing inputs for the regression. Columns are assumed in same order
+                as regression coefficients
+        Returns:
+            result: Resulting data predicted by the regression
+        """
+        result = 0
+        for coefficient, column in zip(self.coefficients[0:-1], input_df.columns):
+            result += coefficient * input_df[column]
+        result += self.coefficients[-1] * np.ones_like(input_df.index)
+        return result
+
+    @staticmethod
+    def quality(predicted, measured):
+        """
+        Perform some quality metrics against some predicted and measured data
+        Args:
+            predicted: Series of predicted data
+            measured: Series of measured data (same length as predicted)
+        Returns:
+            dictionary of varius performance metrics
+        """
+        m_mean = measured.mean()
+        p_mean = predicted.mean()
+        diff = p_mean - m_mean
+
+        # Perform point by point metrics
+        series_difference = predicted - measured
+        p_difference = series_difference / measured
+
+        # Comparisons against absolute values
+        abs_diff = abs(series_difference)
+        p_abs_diff = abs_diff / measured
+
+        return {"mean difference":{'value':diff, "percent": diff / m_mean},
+                # point by point differences
+                'mean point error': {'value':series_difference.mean(), 'percent':p_difference.mean()},
+                'max point error': {'value':series_difference.max(),'percent': p_difference.max()},
+                'min point error': {'value':series_difference.min(),'percent':p_difference.min()},
+                # Absolute value
+                'mean absolute point error': {'value': abs_diff.mean(), 'percent': p_abs_diff.mean()},
+                'max absolute point error': {'value': abs_diff.max(), 'percent': p_abs_diff.max()},
+                'min absolute point error': {'value': abs_diff.min(), 'percent': p_abs_diff.min()},
+                }
+
+    @staticmethod
+    def quality_report(results):
+        """
+        Args:
+            results: Dictionary from quality function
+        Returns:
+            string of quality info
+        """
+        string_report = ''
+        for k,v in results.items():
+            string_report += f"{k.title()} = {v['value']:0.2f} ({v['percent']:0.2%})\n"
+        return string_report
+
+    def get_equation_string(self, rendered=False):
+        """
+        Generate the string representation for the equation.
+        Args:
+            rendered: Keep any render indicators like $ \ etc to get greek repr and various subscripts to be rendered in things
+                like matplotlib. Otherwise remove them.
+        Returns:
+            equation: string equation
+        """
+        # No coefficients available, then there is no known fit
+        if not self.coefficients:
+            result = f'{self.name.title()} (Pre-fit)'
+        else:
+            result = f"{self.name} = "
+            i = 0
+            for c, v in zip(self.coefficients, self.coefficient_names):
+                c_str = f"{abs(c):0.3f}"
+
+                if v:
+                    term = rf"{c_str}*{v}"
+
+                else:
+                    term = c_str
+
+                if i == 0:
+                    joiner = ''
+                else:
+                    if c < 0:
+                        joiner = ' - '
+                    else:
+                        joiner = ' + '
+
+                result += f'{joiner}{term}'
+                i += 1
+
+        if not rendered:
+            result = result.replace('$', '').replace("\\", '')
+
+        return result
+
+    def __repr__(self):
+        return f'Linear Regression (N = {self.n_points}): {self.equation}'
\ No newline at end of file
diff --git a/study_lyte/styles.py b/study_lyte/styles.py
index 32b3dad..c796769 100644
--- a/study_lyte/styles.py
+++ b/study_lyte/styles.py
@@ -9,7 +9,11 @@ class EventStyle(Enum):
     START = 'g', '--', 1
     STOP = 'r', '--',  1
     SURFACE = 'lightsteelblue', '--', 1
+    GROUND = 'sienna', '--', 1
     ERROR = 'orangered', 'dotted',   1
+    IMPACT = 'cyan', 'dotted',   1
+    LONG_PRESS = 'magenta', 'dotted',   1
+
     UNKNOWN = 'k', '--', 1
 
     @classmethod
diff --git a/tests/data/ground_touch_and_go.csv b/tests/data/ground_touch_and_go.csv
new file mode 100644
index 0000000..bb8dc3e
--- /dev/null
+++ b/tests/data/ground_touch_and_go.csv
@@ -0,0 +1,31852 @@
+RECORDED = 2023-12-21--11:28:50
+radicl VERSION = 0.9.1
+FIRMWARE REVISION = 1.46
+HARDWARE REVISION = 1
+MODEL NUMBER = 3
+SAMPLE RATE = 16000
+ZPFO = 50
+ACC. Range = 16
+Serial Num. = 252813070A020004
+Latitude = 43.961
+Longitude = -115.693
+time,Sensor1,Sensor2,Sensor3,Sensor4,depth,X-Axis,Y-Axis,Z-Axis
+0.0,3650,2824,4093,4091,-20.8984375,0.032850000000000004,-0.99061,0.10658
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diff --git a/tests/data/mores_20230119.csv b/tests/data/mores_20230119.csv
new file mode 100644
index 0000000..2399821
--- /dev/null
+++ b/tests/data/mores_20230119.csv
@@ -0,0 +1,39050 @@
+RECORDED = 2023-01-19--12:48:02
+radicl VERSION = 0.6.0
+FIRMWARE REVISION = 1.46
+HARDWARE REVISION = 1
+MODEL NUMBER = 3
+SAMPLE RATE = 16000
+ZPFO = 85
+ACC. Range = 16
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+0.8948958697730824,2037.0,18.0,3183.0,2.0,-61.452107934907836,-0.03851085889570552,-2.3950762576687117,-0.022047791411042947
+0.8949583712306723,2023.0,16.0,3200.0,2.0,-61.46639634936636,-0.03290822085889572,-2.390548466257669,-0.020081717791411047
+0.8950208726882624,2030.0,16.0,3191.0,2.0,-61.48068476382488,-0.027305582822085894,-2.386020674846626,-0.018115644171779147
+0.8950833741458523,2021.0,20.0,3174.0,4.0,-61.49497317828341,-0.021702944785276068,-2.3814928834355826,-0.016149570552147247
+0.8951458756034423,2005.0,18.0,3160.0,2.0,-61.509261592741936,-0.01610030674846627,-2.3769650920245398,-0.014183496932515346
+0.8952083770610322,1978.0,18.0,3158.0,3.0,-61.52355000720046,-0.010497668711656444,-2.372437300613497,-0.012217423312883446
+0.8952708785186222,1979.0,17.0,3167.0,2.0,-61.53783842165899,-0.0048950306748466454,-2.367909509202454,-0.010251349693251546
+0.8953333799762121,1996.0,18.0,3158.0,2.0,-61.55212683611751,0.0007076073619631806,-2.363381717791411,-0.008285276073619632
+0.8953958814338021,1973.0,20.0,3160.0,2.0,-61.566415250576036,0.006310245398773007,-2.358853926380368,-0.006319202453987732
+0.895458382891392,1987.0,22.0,3173.0,1.0,-61.58070366503456,0.011912883435582805,-2.354326134969325,-0.004353128834355832
+0.895520884348982,1990.0,20.0,3150.0,2.0,-61.59499207949309,0.01751552147239263,-2.349798343558282,-0.002387055214723932
+0.895583385806572,1993.0,19.0,3161.0,4.0,-61.609280493951616,0.023118159509202457,-2.3452705521472392,-0.00042098159509203203
+0.8956458872641619,1999.0,18.0,3159.0,1.0,-61.623568908410135,0.028720797546012256,-2.3407427607361964,0.001545092024539868
+0.895708388721752,2002.0,19.0,3162.0,2.0,-61.63785732286866,0.03432343558282208,-2.3362149693251535,0.003511165644171768
+0.8957708901793419,2006.0,16.0,3155.0,2.0,-61.65214573732719,0.03992607361963191,-2.33168717791411,0.005477239263803682
+0.8958333916369319,2050.0,14.0,3164.0,2.0,-61.666434151785715,0.045528711656441734,-2.3271593865030673,0.007443312883435582
+0.8958958930945218,2035.0,16.0,3186.0,3.0,-61.68072256624424,0.051131349693251504,-2.3226315950920244,0.009409386503067482
+0.8959583945521118,2017.0,16.0,3195.0,2.0,-61.69501098070276,0.05673398773006133,-2.3181038036809816,0.011375460122699382
+0.8960208960097017,2026.0,16.0,3195.0,3.0,-61.70929939516129,0.062336625766871157,-2.3135760122699387,0.013341533742331282
+0.8960833974672917,2031.0,17.0,3195.0,3.0,-61.723587809619815,0.06793926380368098,-2.309048220858896,0.015307607361963183
+0.8961458989248816,2029.0,18.0,3183.0,2.0,-61.73787622407834,0.07354190184049081,-2.3045204294478525,0.017273680981595083
+0.8962084003824716,2011.0,16.0,3165.0,2.0,-61.75216463853687,0.07914453987730058,-2.2999926380368096,0.019239754601226983
+0.8962709018400615,2045.0,16.0,3202.0,2.0,-61.76645305299539,0.0847471779141104,-2.2954648466257668,0.021205828220858883
+0.8963334032976515,2031.0,17.0,3213.0,2.0,-61.780741467453915,0.09034981595092023,-2.290937055214724,0.023171901840490797
+0.8963959047552414,2053.0,14.0,3187.0,2.0,-61.79502988191244,0.09595245398773006,-2.286409263803681,0.025137975460122697
+0.8964584062128315,2040.0,18.0,3189.0,2.0,-61.80931829637097,0.10155509202453988,-2.281881472392638,0.027104049079754597
+0.8965209076704215,2058.0,19.0,3192.0,2.0,-61.823606710829495,0.10715773006134971,-2.277353680981595,0.029070122699386497
+0.8965834091280114,2043.0,18.0,3182.0,3.0,-61.83789512528802,0.11276036809815948,-2.272825889570552,0.031036196319018397
+0.8966459105856014,2032.0,16.0,3177.0,1.0,-61.85218353974654,0.1183630061349693,-2.268298098159509,0.0330022699386503
+0.8967084120431913,2040.0,16.0,3166.0,2.0,-61.86647195420507,0.12396564417177913,-2.2637703067484662,0.0349683435582822
+0.8967709135007813,2037.0,16.0,3161.0,1.0,-61.880760368663594,0.12956828220858896,-2.2592425153374234,0.03693441717791411
+0.8968334149583712,2066.0,18.0,3165.0,2.0,-61.89504878312212,0.13517092024539878,-2.25471472392638,0.03890049079754601
+0.8968959164159612,2049.0,18.0,3157.0,2.0,-61.90933719758065,0.14077355828220856,-2.250186932515337,0.04086656441717791
+0.8969584178735511,2041.0,17.0,3187.0,4.0,-61.92362561203917,0.14637619631901838,-2.2456591411042943,0.04283263803680981
+0.8970209193311411,2052.0,15.0,3170.0,2.0,-61.937914026497694,0.1519788343558282,-2.2411313496932515,0.04479871165644171
+0.897083420788731,2040.0,19.0,3158.0,0.0,-61.95220244095622,0.15758147239263803,-2.2366035582822086,0.046764785276073625
+0.8971459222463211,2031.0,17.0,3139.0,2.0,-61.96649085541475,0.16318411042944786,-2.2320757668711657,0.04873085889570551
+0.897208423703911,2049.0,20.0,3130.0,2.0,-61.980779269873274,0.16878674846625763,-2.227547975460123,0.050696932515337426
+0.897270925161501,2046.0,16.0,3145.0,3.0,-61.9950676843318,0.17438938650306746,-2.2230201840490795,0.05266300613496931
+0.8973334266190909,2035.0,14.0,3158.0,2.0,-62.00935609879032,0.17999202453987728,-2.2184923926380367,0.054629079754601226
+0.8973959280766809,2063.0,16.0,3150.0,2.0,-62.02364451324885,0.1855946625766871,-2.213964601226994,0.05659515337423311
+0.8974584295342709,2045.0,19.0,3150.0,4.0,-62.037932927707374,0.19119730061349693,-2.209436809815951,0.058561226993865026
+0.8975209309918608,2037.0,17.0,3163.0,2.0,-62.0522213421659,0.1967999386503067,-2.204909018404908,0.06052730061349691
+0.8975834324494508,2022.0,18.0,3158.0,3.0,-62.06650975662443,0.20240257668711653,-2.2003812269938647,0.062493374233128826
+0.8976459339070407,1997.0,16.0,3142.0,2.0,-62.08079817108295,0.20800521472392636,-2.195853435582822,0.06445944785276074
+0.8977084353646307,2007.0,18.0,3159.0,2.0,-62.09508658554147,0.21360785276073618,-2.191325644171779,0.06642552147239263
+0.8977124183006536,2015.5,18.5,3158.0,2.5,-62.109375,0.219210490797546,-2.186797852760736,0.06839159509202454
+0.8977709368222206,2024.0,19.0,3157.0,3.0,-62.1235035083912,0.22481312883435584,-2.1822700613496933,0.07035766871165643
+0.8978334382798107,2056.0,18.0,3184.0,1.0,-62.137632016782405,0.2304157668711656,-2.1777422699386504,0.07232374233128834
+0.8978959397374006,2045.0,17.0,3164.0,2.0,-62.151760525173614,0.23601840490797543,-2.173214478527607,0.07428981595092023
+0.8979584411949906,2031.0,18.0,3187.0,4.0,-62.16588903356482,0.24162104294478526,-2.168686687116564,0.07625588957055214
+0.8980209426525805,2037.0,14.0,3165.0,2.0,-62.18001754195602,0.24722368098159508,-2.1641588957055213,0.07822196319018405
+0.8980834441101705,2035.0,17.0,3167.0,3.0,-62.19414605034722,0.2528263190184049,-2.1596311042944785,0.08018803680981594
+0.8981459455677604,2028.0,18.0,3183.0,2.0,-62.208274558738424,0.2584289570552147,-2.1551033128834356,0.08215411042944785
+0.8982084470253504,2065.0,18.0,3184.0,2.0,-62.222403067129626,0.2640315950920245,-2.1505755214723923,0.08412018404907974
+0.8982709484829404,2033.0,15.0,3194.0,2.0,-62.236531575520836,0.26963423312883433,-2.1460477300613494,0.08608625766871165
+0.8983334499405303,2024.0,14.0,3200.0,2.0,-62.25066008391204,0.27523687116564416,-2.1415199386503065,0.08805233128834354
+0.8983959513981203,2049.0,16.0,3176.0,2.0,-62.26478859230324,0.280839509202454,-2.1369921472392637,0.09001840490797546
+0.8984584528557102,2034.0,16.0,3171.0,2.0,-62.27891710069444,0.2864421472392638,-2.132464355828221,0.09198447852760737
+0.8985209543133003,2077.0,14.0,3182.0,1.0,-62.293045609085645,0.2920447852760736,-2.127936564417178,0.09395055214723926
+0.8985834557708902,2048.0,20.0,3195.0,7.0,-62.307174117476855,0.29764742331288346,-2.123408773006135,0.09591662576687117
+0.8986459572284802,1999.0,16.0,3165.0,2.0,-62.32130262586806,0.3032500613496932,-2.1188809815950918,0.09788269938650306
+0.8987084586860701,2012.0,18.0,3174.0,4.0,-62.33543113425926,0.308852699386503,-2.114353190184049,0.09984877300613497
+0.8987709601436601,2027.0,19.0,3161.0,2.0,-62.34955964265046,0.31445533742331283,-2.109825398773006,0.10181484662576686
+0.89883346160125,2026.0,18.0,3170.0,3.0,-62.363688151041664,0.32005797546012266,-2.105297607361963,0.10378092024539877
+0.89889596305884,2033.0,18.0,3157.0,2.0,-62.377816659432874,0.3256606134969325,-2.1007698159509203,0.10574699386503066
+0.8989584645164299,2013.0,16.0,3122.0,2.0,-62.391945167824076,0.3312632515337423,-2.096242024539877,0.10771306748466257
+0.8990209659740199,2011.0,17.0,3144.0,2.0,-62.40607367621528,0.33686588957055214,-2.091714233128834,0.10967914110429448
+0.8990834674316098,2021.0,22.0,3149.0,3.0,-62.42020218460648,0.34246852760736196,-2.087186441717791,0.11164521472392637
+0.8991459688891998,2024.0,17.0,3154.0,2.0,-62.43433069299768,0.3480711656441718,-2.0826586503067483,0.11361128834355828
+0.8992084703467899,2070.0,20.0,3166.0,4.0,-62.448459201388886,0.3536738036809816,-2.0781308588957055,0.11557736196319017
+0.8992709718043798,2035.0,14.0,3169.0,2.0,-62.462587709780095,0.35927644171779144,-2.0736030674846626,0.11754343558282208
+0.8993334732619698,2023.0,13.0,3192.0,2.0,-62.4767162181713,0.36487907975460115,-2.0690752760736197,0.11950950920245397
+0.8993959747195597,2052.0,16.0,3173.0,2.0,-62.4908447265625,0.370481717791411,-2.0645474846625764,0.12147558282208588
+0.8994584761771497,2031.0,18.0,3179.0,2.0,-62.5049732349537,0.3760843558282208,-2.0600196932515336,0.12344165644171777
+0.8995209776347396,2064.0,18.0,3208.0,2.0,-62.519101743344905,0.38168699386503063,-2.0554919018404907,0.1254077300613497
+0.8995834790923296,2041.0,16.0,3208.0,6.0,-62.533230251736114,0.38728963190184046,-2.050964110429448,0.1273738036809816
+0.8996459805499195,2026.0,18.0,3225.0,2.0,-62.54735876012732,0.3928922699386503,-2.046436319018405,0.12933987730061347
+0.8997084820075095,2052.0,17.0,3206.0,4.0,-62.56148726851852,0.3984949079754601,-2.0419085276073616,0.13130595092024538
+0.8997709834650994,2035.0,17.0,3206.0,2.0,-62.57561577690972,0.40409754601226994,-2.0373807361963188,0.1332720245398773
+0.8998334849226894,2054.0,18.0,3230.0,2.0,-62.589744285300924,0.40970018404907976,-2.032852944785276,0.1352380981595092
+0.8998959863802793,2013.0,17.0,3205.0,2.0,-62.603872793692126,0.4153028220858896,-2.028325153374233,0.13720417177914107
+0.8999584878378694,2077.0,16.0,3212.0,2.0,-62.618001302083336,0.4209054601226994,-2.02379736196319,0.13917024539877298
+0.9000209892954594,2046.0,14.0,3201.0,2.0,-62.63212981047454,0.42650809815950913,-2.0192695705521473,0.1411363190184049
+0.9000834907530493,2032.0,18.0,3212.0,2.0,-62.64625831886574,0.43211073619631896,-2.0147417791411044,0.1431023926380368
+0.9001459922106393,2029.0,18.0,3174.0,3.0,-62.66038682725694,0.4377133742331288,-2.010213987730061,0.14506846625766873
+0.9002084936682292,2070.0,19.0,3171.0,2.0,-62.674515335648145,0.4433160122699386,-2.0056861963190182,0.14703453987730059
+0.9002709951258192,2037.0,16.0,3186.0,2.0,-62.688643844039355,0.44891865030674843,-2.0011584049079754,0.1490006134969325
+0.9003334965834091,2018.0,16.0,3194.0,2.0,-62.70277235243056,0.45452128834355826,-1.9966306134969325,0.1509666871165644
+0.9003959980409991,2024.0,16.0,3200.0,3.0,-62.71690086082176,0.4601239263803681,-1.9921028220858894,0.15293276073619633
+0.900458499498589,2026.0,18.0,3179.0,2.0,-62.73102936921296,0.4657265644171779,-1.9875750306748465,0.15489883435582824
+0.900521000956179,2004.0,19.0,3178.0,2.0,-62.745157877604164,0.47132920245398774,-1.9830472392638034,0.1568649079754601
+0.9005835024137689,2021.0,20.0,3196.0,2.0,-62.759286385995374,0.47693184049079757,-1.9785194478527606,0.158830981595092
+0.900646003871359,1992.0,16.0,3174.0,2.0,-62.773414894386576,0.4825344785276073,-1.9739916564417177,0.16079705521472393
+0.9007085053289489,2005.0,11.0,3178.0,3.0,-62.78754340277778,0.4881371165644171,-1.9694638650306748,0.16276312883435584
+0.9007710067865389,2018.0,19.0,3171.0,4.0,-62.80167191116898,0.49373975460122693,-1.9649360736196317,0.1647292024539877
+0.9008335082441288,1983.0,21.0,3190.0,2.0,-62.81580041956018,0.49934239263803676,-1.9604082822085886,0.1666952760736196
+0.9008960097017188,2012.0,20.0,3196.0,2.0,-62.829928927951386,0.5049450306748466,-1.9558804907975458,0.16866134969325153
+0.9009585111593088,1987.0,18.0,3168.0,1.0,-62.844057436342595,0.5105476687116564,-1.951352699386503,0.17062742331288344
+0.9010210126168987,1998.0,17.0,3177.0,2.0,-62.8581859447338,0.5161503067484663,-1.94682490797546,0.17259349693251536
+0.9010835140744887,2019.0,18.0,3171.0,2.0,-62.872314453125,0.521752944785276,-1.9422971165644172,0.17455957055214727
+0.9011460155320786,2026.0,17.0,3192.0,2.0,-62.8864429615162,0.5273555828220859,-1.937769325153374,0.17652564417177913
+0.9012085169896686,2074.0,16.0,3206.0,2.0,-62.900571469907405,0.5329582208588957,-1.933241533742331,0.17849171779141104
+0.9012710184472585,2037.0,20.0,3208.0,4.0,-62.914699978298614,0.5385608588957056,-1.9287137423312881,0.18045779141104296
+0.9013335199048486,1997.0,18.0,3181.0,3.0,-62.92882848668982,0.5441634969325153,-1.9241859509202452,0.18242386503067487
+0.9013960213624385,2006.0,17.0,3182.0,2.0,-62.94295699508102,0.549766134969325,-1.9196581595092024,0.18438993865030673
+0.9014585228200285,2021.0,17.0,3179.0,2.0,-62.95708550347222,0.555368773006135,-1.9151303680981593,0.18635601226993864
+0.9015210242776184,1990.0,24.0,3183.0,2.0,-62.971214011863424,0.5609714110429447,-1.9106025766871164,0.18832208588957056
+0.9015835257352084,2035.0,18.0,3200.0,3.0,-62.985342520254626,0.5665740490797546,-1.9060747852760733,0.19028815950920247
+0.9016460271927983,1991.0,20.0,3200.0,2.0,-62.999471028645836,0.5721766871165643,-1.9015469938650305,0.19225423312883438
+0.9017085286503883,2015.0,17.0,3191.0,2.0,-63.01359953703704,0.5777793251533743,-1.8970192024539876,0.19422030674846624
+0.9017710301079783,1986.0,19.0,3188.0,4.0,-63.02772804542824,0.583381963190184,-1.8924914110429447,0.19618638036809816
+0.9018335315655682,1995.0,16.0,3180.0,1.0,-63.04185655381944,0.5889846012269939,-1.8879636196319016,0.19815245398773007
+0.9018960330231582,2010.0,17.0,3170.0,3.0,-63.055985062210645,0.5945872392638036,-1.8834358282208588,0.20011852760736198
+0.9019585344807481,1975.0,24.0,3158.0,2.0,-63.070113570601855,0.6001898773006134,-1.8789080368098157,0.20208460122699384
+0.9020210359383382,2003.0,18.0,3159.0,2.0,-63.08424207899306,0.6057925153374233,-1.8743802453987728,0.20405067484662576
+0.9020835373959281,1987.0,18.0,3130.0,2.0,-63.09837058738426,0.611395153374233,-1.86985245398773,0.20601674846625767
+0.9021460388535181,2017.0,16.0,3153.0,2.0,-63.11249909577546,0.6169977914110429,-1.865324662576687,0.20798282208588958
+0.902208540311108,2018.0,15.0,3193.0,2.0,-63.126627604166664,0.6226004294478527,-1.860796871165644,0.2099488957055215
+0.902271041768698,2051.0,15.0,3189.0,2.0,-63.140756112557874,0.6282030674846626,-1.856269079754601,0.21191496932515336
+0.9023335432262879,2031.0,15.0,3191.0,2.0,-63.154884620949076,0.6338057055214723,-1.851741288343558,0.21388104294478527
+0.9023960446838779,2058.0,18.0,3212.0,2.0,-63.16901312934028,0.6394083435582822,-1.8472134969325151,0.21584711656441719
+0.9024585461414678,2045.0,17.0,3197.0,1.0,-63.18314163773148,0.645010981595092,-1.8426857055214723,0.2178131901840491
+0.9025210475990578,2033.0,16.0,3216.0,2.0,-63.19727014612268,0.6506136196319019,-1.8381579141104294,0.219779263803681
+0.9025835490566477,2004.0,17.0,3190.0,2.0,-63.211398654513886,0.6562162576687116,-1.8336301226993863,0.22174533742331287
+0.9026460505142377,2023.0,16.0,3193.0,4.0,-63.225527162905095,0.6618188957055213,-1.8291023312883432,0.22371141104294479
+0.9027085519718278,1994.0,22.0,3187.0,2.0,-63.2396556712963,0.6674215337423313,-1.8245745398773003,0.2256774846625767
+0.9027710534294177,2018.0,19.0,3178.0,3.0,-63.2537841796875,0.673024171779141,-1.8200467484662575,0.2276435582822086
+0.9028335548870077,2011.0,14.0,3160.0,2.0,-63.2679126880787,0.6786268098159509,-1.8155189570552146,0.22960963190184047
+0.9028960563445976,2015.0,17.0,3183.0,2.0,-63.282041196469905,0.6842294478527606,-1.8109911656441717,0.23157570552147239
+0.9029585578021876,2045.0,16.0,3211.0,2.0,-63.296169704861114,0.6898320858895706,-1.8064633742331286,0.2335417791411043
+0.9030210592597775,2068.0,14.0,3212.0,3.0,-63.31029821325232,0.6954347239263803,-1.8019355828220855,0.2355078527607362
+0.9030835607173675,2057.0,16.0,3195.0,2.0,-63.32442672164352,0.7010373619631902,-1.7974077914110427,0.23747392638036813
+0.903114186851211,2051.0,17.0,3194.5,4.0,-63.33855523003472,0.7066399999999999,-1.7928799999999998,0.23944
+0.9031460621749574,2045.0,18.0,3194.0,6.0,-63.352683738425924,0.6983323312883435,-1.7831347239263802,0.2424047852760736
+0.9032085636325474,2043.0,19.0,3206.0,2.0,-63.36681224681713,0.690024662576687,-1.7733894478527605,0.24536957055214723
+0.9032710650901373,2054.0,18.0,3202.0,2.0,-63.380940755208336,0.6817169938650306,-1.763644171779141,0.24833435582822083
+0.9033335665477273,2027.0,18.0,3211.0,2.0,-63.39506926359954,0.6734093251533741,-1.7538988957055213,0.25129914110429447
+0.9033960680053172,2037.0,16.0,3206.0,2.0,-63.40919777199074,0.6651016564417177,-1.7441536196319016,0.2542639263803681
+0.9034585694629073,2045.0,16.0,3201.0,2.0,-63.42332628038194,0.6567939877300613,-1.734408343558282,0.2572287116564417
+0.9035210709204973,2012.0,21.0,3206.0,2.0,-63.437454788773145,0.6484863190184048,-1.7246630674846624,0.2601934969325153
+0.9035835723780872,2034.0,18.0,3209.0,1.0,-63.451583297164355,0.6401786503067484,-1.7149177914110427,0.26315828220858895
+0.9036460738356772,2004.0,19.0,3198.0,4.0,-63.46571180555556,0.6318709815950919,-1.705172515337423,0.2661230674846626
+0.9037085752932671,2014.0,16.0,3220.0,2.0,-63.47984031394676,0.6235633128834355,-1.6954272392638035,0.26908785276073616
+0.9037710767508571,2028.0,17.0,3204.0,2.0,-63.49396882233796,0.6152556441717791,-1.6856819631901838,0.2720526380368098
+0.903833578208447,1990.0,23.0,3200.0,3.0,-63.508097330729164,0.6069479754601226,-1.6759366871165642,0.2750174233128834
+0.903896079666037,2022.0,16.0,3212.0,2.0,-63.522225839120374,0.5986403067484662,-1.6661914110429445,0.27798220858895706
+0.9039585811236269,2072.0,18.0,3232.0,2.0,-63.536354347511576,0.5903326380368098,-1.656446134969325,0.28094699386503064
+0.9040210825812169,2052.0,18.0,3221.0,3.0,-63.55048285590278,0.5820249693251534,-1.6467008588957053,0.28391177914110427
+0.9040835840388068,2039.0,17.0,3228.0,3.0,-63.56461136429398,0.5737173006134969,-1.6369555828220856,0.2868765644171779
+0.9041460854963969,2032.0,19.0,3198.0,2.0,-63.57873987268518,0.5654096319018405,-1.627210306748466,0.2898413496932515
+0.9042085869539868,2008.0,19.0,3192.0,3.0,-63.592868381076386,0.557101963190184,-1.6174650306748464,0.2928061349693251
+0.9042710884115768,2018.0,20.0,3185.0,2.0,-63.606996889467595,0.5487942944785276,-1.6077197546012267,0.29577092024539875
+0.9043335898691667,1998.0,18.0,3157.0,2.0,-63.6211253978588,0.5404866257668711,-1.597974478527607,0.2987357055214724
+0.9043960913267567,2007.0,16.0,3174.0,2.0,-63.63525390625,0.5321789570552147,-1.5882292024539875,0.30170049079754596
+0.9044585927843467,2022.0,19.0,3176.0,3.0,-63.6493824146412,0.5238712883435582,-1.5784839263803678,0.3046652760736196
+0.9045210942419366,2003.0,22.0,3169.0,2.0,-63.663510923032405,0.5155636196319018,-1.5687386503067482,0.30763006134969323
+0.9045835956995266,2018.0,18.0,3177.0,3.0,-63.677639431423614,0.5072559509202453,-1.5589933742331286,0.31059484662576686
+0.9046460971571165,2018.0,15.0,3157.0,3.0,-63.69176793981482,0.4989482822085889,-1.549248098159509,0.31355963190184044
+0.9047085986147065,2017.0,17.0,3183.0,3.0,-63.70589644820602,0.49064061349693244,-1.5395028220858893,0.3165244171779141
+0.9047711000722964,2023.0,16.0,3189.0,2.0,-63.72002495659722,0.482332944785276,-1.5297575460122697,0.3194892024539877
+0.9048336015298865,2029.0,16.0,3205.0,3.0,-63.734153464988424,0.47402527607361955,-1.52001226993865,0.3224539877300613
+0.9048961029874764,2027.0,18.0,3199.0,7.0,-63.74828197337963,0.4657176073619631,-1.5102669938650304,0.3254187730061349
+0.9049586044450664,2068.0,15.0,3188.0,2.0,-63.762410481770836,0.4574099386503067,-1.5005217177914107,0.32838355828220855
+0.9050211059026563,2034.0,18.0,3204.0,4.0,-63.77653899016204,0.44910226993865027,-1.4907764417177911,0.3313483435582822
+0.9050836073602463,2025.0,13.0,3224.0,3.0,-63.79066749855324,0.4407946012269938,-1.4810311656441715,0.3343131288343558
+0.9051461088178362,2030.0,18.0,3214.0,2.0,-63.80479600694444,0.4324869325153374,-1.4712858895705518,0.3372779141104294
+0.9052086102754262,1987.0,20.0,3219.0,3.0,-63.818924515335645,0.42417926380368093,-1.4615406134969322,0.34024269938650303
+0.9052711117330162,2021.0,16.0,3214.0,2.0,-63.833053023726855,0.4158715950920245,-1.4517953374233126,0.34320748466257667
+0.9053336131906061,2062.0,19.0,3237.0,2.0,-63.84718153211806,0.40756392638036804,-1.442050061349693,0.34617226993865025
+0.9053961146481961,2040.0,20.0,3243.0,7.0,-63.86131004050926,0.3992562576687116,-1.4323047852760733,0.3491370552147239
+0.905458616105786,2019.0,16.0,3271.0,2.0,-63.87543854890046,0.3909485889570552,-1.4225595092024537,0.3521018404907975
+0.905521117563376,2038.0,17.0,3270.0,4.0,-63.889567057291664,0.38264092024539875,-1.412814233128834,0.35506662576687115
+0.905583619020966,2008.0,17.0,3235.0,2.0,-63.903695565682874,0.3743332515337423,-1.4030689570552144,0.3580314110429448
+0.905646120478556,1990.0,22.0,3242.0,3.0,-63.917824074074076,0.36602558282208586,-1.393323680981595,0.36099619631901836
+0.9057086219361459,1983.0,18.0,3251.0,2.0,-63.93195258246528,0.3577179141104294,-1.3835784049079753,0.363960981595092
+0.9057711233937359,2021.0,14.0,3239.0,2.0,-63.94608109085648,0.34941024539877297,-1.3738331288343557,0.3669257668711656
+0.9058336248513258,1988.0,16.0,3255.0,2.0,-63.96020959924768,0.3411025766871165,-1.364087852760736,0.3698905521472392
+0.9058961263089158,1985.0,14.0,3261.0,4.0,-63.974338107638886,0.3327949079754601,-1.3543425766871164,0.37285533742331284
+0.9059586277665057,2005.0,16.0,3255.0,2.0,-63.988466616030095,0.32448723926380363,-1.3445973006134968,0.37582012269938647
+0.9060211292240957,1989.0,17.0,3257.0,2.0,-64.00259512442129,0.3161795705521472,-1.3348520245398772,0.37878490797546005
+0.9060836306816856,2036.0,14.0,3256.0,2.0,-64.0167236328125,0.30787190184049074,-1.3251067484662575,0.3817496932515337
+0.9061461321392756,1985.0,18.0,3239.0,2.0,-64.03085214120371,0.29956423312883435,-1.315361472392638,0.3847144785276073
+0.9062086335968657,1941.0,21.0,3235.0,2.0,-64.0449806495949,0.2912565644171779,-1.3056161963190183,0.3876792638036809
+0.9062711350544556,1963.0,19.0,3235.0,3.0,-64.05910915798611,0.28294889570552145,-1.2958709202453986,0.3906440490797546
+0.9063336365120456,1933.0,18.0,3198.0,2.0,-64.07323766637731,0.274641226993865,-1.286125644171779,0.39360883435582816
+0.9063961379696355,1923.0,16.0,3206.0,2.0,-64.08736617476852,0.26633355828220856,-1.2763803680981594,0.3965736196319018
+0.9064586394272255,1919.0,18.0,3198.0,2.0,-64.10149468315973,0.2580258895705521,-1.2666350920245397,0.39953840490797543
+0.9065211408848154,1868.0,26.0,3198.0,2.0,-64.11562319155092,0.24971822085889567,-1.25688981595092,0.402503190184049
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+0.9311467151752606,1949.0,19.0,3222.0,2.0,-70.079835109447,-0.27973331288343556,-0.4873847239263804,0.46275730061349696
+0.9312092166328506,1938.0,15.0,3223.0,0.0,-70.09659868231567,-0.2806738036809816,-0.48767134969325154,0.4606120858895706
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+0.9313967210056204,1950.0,17.0,3217.0,3.0,-70.14688940092167,-0.28349527607361963,-0.48853122699386503,0.4541764417177914
+0.9314592224632104,1944.0,20.0,3219.0,4.0,-70.16365297379032,-0.2844357668711656,-0.4888178527607362,0.45203122699386505
+0.9315217239208003,1934.0,16.0,3220.0,2.0,-70.18041654665899,-0.28537625766871166,-0.48910447852760736,0.4498860122699387
+0.9315842253783904,1966.0,16.0,3208.0,2.0,-70.19718011952764,-0.28631674846625765,-0.4893911042944785,0.44774079754601226
+0.9316467268359803,1924.0,16.0,3221.0,2.0,-70.21394369239631,-0.28725723926380364,-0.4896777300613497,0.4455955828220859
+0.9317092282935703,1915.0,16.0,3226.0,2.0,-70.23070726526498,-0.2881977300613497,-0.48996435582822084,0.4434503680981595
+0.9317717297511603,1928.0,16.0,3227.0,2.0,-70.24747083813364,-0.2891382208588957,-0.49025098159509206,0.44130515337423315
+0.9318342312087502,1909.0,16.0,3235.0,2.0,-70.2642344110023,-0.2900787116564417,-0.4905376073619632,0.4391599386503068
+0.9318967326663402,1956.0,16.0,3240.0,2.0,-70.28099798387096,-0.2910192024539877,-0.4908242331288344,0.4370147239263804
+0.9319592341239301,1919.0,18.0,3245.0,4.0,-70.29776155673963,-0.2919596932515337,-0.49111085889570555,0.434869509202454
+0.9320217355815201,1907.0,14.0,3265.0,3.0,-70.3145251296083,-0.29290018404907975,-0.4913974846625767,0.4327242944785276
+0.93208423703911,1899.0,14.0,3235.0,2.0,-70.33128870247695,-0.29384067484662574,-0.4916841104294479,0.43057907975460125
+0.9321467384967,1912.0,16.0,3219.0,2.0,-70.34805227534562,-0.2947811656441718,-0.49197073619631904,0.4284338650306749
+0.93220923995429,1899.0,16.0,3208.0,3.0,-70.36481584821429,-0.2957216564417178,-0.4922573619631902,0.4262886503067485
+0.93227174141188,1929.0,16.0,3181.0,2.0,-70.38157942108295,-0.29666214723926376,-0.49254398773006136,0.4241434355828221
+0.9323342428694699,1904.0,15.0,3189.0,3.0,-70.39834299395162,-0.2976026380368098,-0.4928306134969325,0.4219982208588957
+0.9323967443270599,1914.0,14.0,3198.0,2.0,-70.41510656682027,-0.2985431288343558,-0.4931172392638037,0.41985300613496934
+0.9324592457846498,1950.0,19.0,3175.0,4.0,-70.43187013968894,-0.29948361963190184,-0.49340386503067485,0.417707791411043
+0.9325217472422398,1929.0,17.0,3154.0,2.0,-70.44863371255761,-0.30042411042944783,-0.493690490797546,0.4155625766871166
+0.9325842486998298,1966.0,18.0,3180.0,4.0,-70.46539728542626,-0.3013646012269938,-0.4939771165644172,0.41341736196319023
+0.9326467501574197,1946.0,17.0,3182.0,2.0,-70.48216085829493,-0.30230509202453987,-0.49426374233128834,0.4112721472392638
+0.9327092516150097,1940.0,15.0,3183.0,1.0,-70.4989244311636,-0.3032455828220859,-0.49455036809815955,0.40912693251533744
+0.9327717530725996,1967.0,14.0,3155.0,2.0,-70.51568800403226,-0.3041860736196319,-0.49483699386503066,0.40698171779141107
+0.9328342545301896,1954.0,16.0,3137.0,1.0,-70.53245157690093,-0.3051265644171779,-0.4951236196319019,0.4048365030674847
+0.9328967559877795,1972.0,18.0,3154.0,2.0,-70.54921514976958,-0.3060670552147239,-0.49541024539877304,0.40269128834355833
+0.9329592574453696,1965.0,19.0,3139.0,5.0,-70.56597872263825,-0.3070075460122699,-0.4956968711656442,0.4005460736196319
+0.9330217589029595,1952.0,16.0,3140.0,2.0,-70.58274229550692,-0.307948036809816,-0.49598349693251537,0.39840085889570553
+0.9330842603605495,1966.0,16.0,3114.0,4.0,-70.59950586837557,-0.30888852760736196,-0.49627012269938653,0.39625564417177916
+0.9331467618181394,1960.0,18.0,3083.0,2.0,-70.61626944124424,-0.30982901840490795,-0.4965567484662577,0.3941104294478528
+0.9332092632757294,1954.0,18.0,3064.0,2.0,-70.6330330141129,-0.31076950920245394,-0.49684337423312885,0.3919652147239264
+0.9332179930795848,1979.5,15.5,3063.5,2.0,-70.64979658698157,-0.31171,-0.49713,0.38982
+0.9332717647333193,2005.0,13.0,3063.0,2.0,-70.66656015985023,-0.3109214197530864,-0.49307895061728396,0.3879904938271605
+0.9333342661909093,1975.0,16.0,3070.0,1.0,-70.68332373271889,-0.3101328395061728,-0.4890279012345679,0.386160987654321
+0.9333967676484992,1928.0,17.0,3038.0,3.0,-70.70008730558756,-0.30934425925925924,-0.48497685185185185,0.3843314814814815
+0.9334592691060892,1965.0,19.0,3062.0,7.0,-70.71685087845623,-0.30855567901234565,-0.4809258024691358,0.382501975308642
+0.9335217705636792,1975.0,16.0,3028.0,2.0,-70.73361445132488,-0.30776709876543207,-0.4768747530864198,0.3806724691358025
+0.9335842720212691,1940.0,32.0,2992.0,4.0,-70.75037802419355,-0.3069785185185185,-0.47282370370370375,0.37884296296296294
+0.9336467734788592,1992.0,18.0,3056.0,3.0,-70.7671415970622,-0.3061899382716049,-0.4687726543209877,0.37701345679012344
+0.9337092749364491,2047.0,15.0,3053.0,2.0,-70.78390516993088,-0.30540135802469137,-0.46472160493827164,0.37518395061728393
+0.9337717763940391,2005.0,17.0,3038.0,2.0,-70.80066874279954,-0.3046127777777778,-0.4606705555555556,0.37335444444444443
+0.933834277851629,2005.0,12.0,3041.0,2.0,-70.8174323156682,-0.3038241975308642,-0.45661950617283953,0.37152493827160493
+0.933896779309219,2060.0,15.0,3077.0,2.0,-70.83419588853687,-0.3030356172839506,-0.4525684567901235,0.36969543209876543
+0.9339592807668089,2023.0,19.0,3044.0,4.0,-70.85095946140552,-0.30224703703703704,-0.4485174074074074,0.36786592592592593
+0.9340217822243989,2026.0,18.0,3021.0,2.0,-70.86772303427419,-0.30145845679012345,-0.44446635802469137,0.36603641975308643
+0.9340842836819888,2052.0,18.0,3085.0,3.0,-70.88448660714286,-0.30066987654320987,-0.4404153086419753,0.3642069135802469
+0.9341467851395788,2028.0,17.0,3077.0,2.0,-70.90125018001152,-0.2998812962962963,-0.43636425925925926,0.3623774074074074
+0.9342092865971687,2011.0,16.0,3044.0,2.0,-70.91801375288019,-0.2990927160493827,-0.4323132098765432,0.3605479012345679
+0.9342717880547587,2004.0,18.0,3026.0,2.0,-70.93477732574885,-0.2983041358024691,-0.42826216049382715,0.3587183950617284
+0.9343342895123488,2001.0,13.0,2995.0,1.0,-70.95154089861751,-0.29751555555555553,-0.42421111111111115,0.3568888888888889
+0.9343967909699387,2030.0,16.0,3042.0,2.0,-70.96830447148618,-0.29672697530864195,-0.4201600617283951,0.35505938271604937
+0.9344592924275287,2058.0,17.0,3019.0,2.0,-70.98506804435483,-0.29593839506172837,-0.41610901234567904,0.35322987654320986
+0.9345217938851186,2038.0,18.0,3051.0,4.0,-71.0018316172235,-0.2951498148148148,-0.412057962962963,0.35140037037037036
+0.9345842953427086,2046.0,16.0,3050.0,2.0,-71.01859519009217,-0.2943612345679012,-0.40800691358024693,0.34957086419753086
+0.9346467968002985,2022.0,20.0,3048.0,2.0,-71.03535876296083,-0.29357265432098767,-0.4039558641975309,0.34774135802469136
+0.9347092982578885,2015.0,17.0,3016.0,3.0,-71.0521223358295,-0.2927840740740741,-0.3999048148148148,0.34591185185185186
+0.9347717997154784,2038.0,16.0,2983.0,2.0,-71.06888590869815,-0.2919954938271605,-0.39585376543209877,0.34408234567901236
+0.9348343011730684,2024.0,16.0,3033.0,2.0,-71.08564948156682,-0.2912069135802469,-0.39180271604938277,0.34225283950617286
+0.9348968026306583,2021.0,14.0,3051.0,2.0,-71.10241305443549,-0.29041833333333333,-0.3877516666666667,0.34042333333333336
+0.9349593040882483,2026.0,18.0,3042.0,0.0,-71.11917662730414,-0.28962975308641975,-0.38370061728395066,0.33859382716049385
+0.9350218055458382,2013.0,17.0,3045.0,4.0,-71.13594020017281,-0.28884117283950617,-0.3796495679012346,0.3367643209876543
+0.9350843070034283,2013.0,21.0,3070.0,2.0,-71.15270377304148,-0.2880525925925926,-0.37559851851851855,0.3349348148148148
+0.9351468084610182,2018.0,18.0,3071.0,2.0,-71.16946734591014,-0.287264012345679,-0.3715474691358025,0.3331053086419753
+0.9352093099186082,2023.0,18.0,3087.0,2.0,-71.1862309187788,-0.2864754320987654,-0.36749641975308645,0.3312758024691358
+0.9352718113761982,2070.0,18.0,3111.0,2.0,-71.20299449164746,-0.28568685185185183,-0.3634453703703704,0.3294462962962963
+0.9353343128337881,2030.0,18.0,3081.0,3.0,-71.21975806451613,-0.28489827160493825,-0.35939432098765434,0.3276167901234568
+0.9353968142913781,2023.0,16.0,3108.0,2.0,-71.2365216373848,-0.28410969135802466,-0.3553432716049383,0.3257872839506173
+0.935459315748968,2048.0,16.0,3092.0,2.0,-71.25328521025345,-0.2833211111111111,-0.35129222222222223,0.3239577777777778
+0.935521817206558,2013.0,20.0,3077.0,5.0,-71.27004878312212,-0.2825325308641975,-0.3472411728395062,0.3221282716049383
+0.9355843186641479,2068.0,18.0,3123.0,2.0,-71.28681235599079,-0.28174395061728397,-0.3431901234567901,0.3202987654320988
+0.9356468201217379,2039.0,16.0,3110.0,2.0,-71.30357592885944,-0.2809553703703704,-0.33913907407407407,0.3184692592592593
+0.9357093215793278,2018.0,17.0,3106.0,2.0,-71.32033950172811,-0.2801667901234568,-0.33508802469135807,0.3166397530864198
+0.9357718230369179,2022.0,13.0,3071.0,2.0,-71.33710307459677,-0.2793782098765432,-0.331036975308642,0.3148102469135803
+0.9358343244945078,2006.0,16.0,3057.0,2.0,-71.35386664746544,-0.27858962962962963,-0.32698592592592596,0.3129807407407408
+0.9358968259520978,2005.0,17.0,3069.0,2.0,-71.3706302203341,-0.27780104938271605,-0.3229348765432099,0.3111512345679012
+0.9359593274096877,2025.0,23.0,3071.0,4.0,-71.38739379320276,-0.27701246913580246,-0.31888382716049385,0.3093217283950617
+0.9360218288672777,2013.0,19.0,3071.0,2.0,-71.40415736607143,-0.2762238888888889,-0.3148327777777778,0.3074922222222222
+0.9360843303248677,2003.0,17.0,3062.0,2.0,-71.42092093894009,-0.2754353086419753,-0.3107817283950618,0.3056627160493827
+0.9361468317824576,2019.0,19.0,3069.0,2.0,-71.43768451180875,-0.2746467283950617,-0.30673067901234574,0.3038332098765432
+0.9362093332400476,2027.0,16.0,3079.0,3.0,-71.45444808467742,-0.27385814814814813,-0.3026796296296297,0.3020037037037037
+0.9362718346976375,2057.0,19.0,3095.0,2.0,-71.47121165754608,-0.27306956790123454,-0.29862858024691363,0.3001741975308642
+0.9363343361552275,2041.0,17.0,3085.0,3.0,-71.48797523041475,-0.27228098765432096,-0.2945775308641976,0.2983446913580247
+0.9363968376128174,1983.0,18.0,3045.0,2.0,-71.50473880328342,-0.27149240740740743,-0.2905264814814815,0.29651518518518516
+0.9364593390704075,2012.0,15.0,3064.0,2.0,-71.52150237615207,-0.2707038271604938,-0.28647543209876547,0.29468567901234566
+0.9365218405279974,2017.0,18.0,3070.0,2.0,-71.53826594902074,-0.26991524691358026,-0.2824243827160494,0.29285617283950616
+0.9365843419855874,2017.0,16.0,3063.0,2.0,-71.5550295218894,-0.2691266666666667,-0.27837333333333336,0.29102666666666666
+0.9366468434431773,2012.0,19.0,3059.0,2.0,-71.57179309475806,-0.2683380864197531,-0.2743222839506173,0.28919716049382715
+0.9367093449007673,2061.0,16.0,3068.0,5.0,-71.58855666762673,-0.2675495061728395,-0.27027123456790125,0.28736765432098765
+0.9367718463583572,2015.0,19.0,3071.0,2.0,-71.60532024049539,-0.26676092592592593,-0.2662201851851852,0.28553814814814815
+0.9368343478159472,2004.0,20.0,3066.0,0.0,-71.62208381336406,-0.26597234567901235,-0.26216913580246914,0.28370864197530865
+0.9368968492735371,1961.0,32.0,3073.0,2.0,-71.63884738623273,-0.26518376543209876,-0.2581180864197531,0.28187913580246915
+0.9369593507311271,1988.0,22.0,3075.0,2.0,-71.65561095910138,-0.2643951851851852,-0.25406703703703704,0.28004962962962965
+0.9370218521887171,1971.0,17.0,3058.0,2.0,-71.67237453197005,-0.2636066049382716,-0.250015987654321,0.27822012345679015
+0.937084353646307,1975.0,17.0,3089.0,2.0,-71.6891381048387,-0.262818024691358,-0.24596493827160498,0.27639061728395065
+0.9371468551038971,2005.0,16.0,3094.0,2.0,-71.70590167770737,-0.2620294444444444,-0.24191388888888893,0.27456111111111114
+0.937209356561487,2015.0,19.0,3107.0,4.0,-71.72266525057604,-0.26124086419753084,-0.23786283950617287,0.27273160493827164
+0.937271858019077,2031.0,20.0,3112.0,2.0,-71.7394288234447,-0.26045228395061726,-0.23381179012345682,0.27090209876543214
+0.9373343594766669,2018.0,19.0,3114.0,2.0,-71.75619239631337,-0.25966370370370373,-0.22976074074074077,0.2690725925925926
+0.9373968609342569,1978.0,18.0,3091.0,2.0,-71.77295596918202,-0.25887512345679015,-0.2257096913580247,0.2672430864197531
+0.9374593623918468,1976.0,18.0,3126.0,2.0,-71.78971954205069,-0.25808654320987656,-0.22165864197530866,0.2654135802469136
+0.9375218638494368,1989.0,24.0,3121.0,1.0,-71.80648311491936,-0.257297962962963,-0.2176075925925926,0.2635840740740741
+0.9375843653070267,1976.0,20.0,3131.0,2.0,-71.82324668778801,-0.2565093827160494,-0.2135565432098766,0.2617545679012346
+0.9376468667646167,1986.0,18.0,3143.0,2.0,-71.84001026065668,-0.2557208024691358,-0.20950549382716055,0.2599250617283951
+0.9377093682222066,2044.0,17.0,3163.0,4.0,-71.85677383352535,-0.2549322222222222,-0.2054544444444445,0.2580955555555556
+0.9377718696797966,2015.0,18.0,3167.0,3.0,-71.87353740639401,-0.25414364197530864,-0.20140339506172844,0.256266049382716
+0.9378343711373867,1986.0,21.0,3138.0,2.0,-71.89030097926268,-0.25335506172839506,-0.1973523456790124,0.2544365432098765
+0.9378968725949766,1954.0,24.0,3139.0,2.0,-71.90706455213133,-0.2525664814814815,-0.19330129629629633,0.252607037037037
+0.9379084967320263,1964.5,21.0,3143.0,1.5,-71.923828125,-0.2517779012345679,-0.18925024691358028,0.2507775308641975
+0.9379593740525666,1975.0,18.0,3147.0,1.0,-71.94066930700231,-0.2509893209876543,-0.18519919753086422,0.24894802469135804
+0.9380218755101565,1967.0,19.0,3129.0,3.0,-71.95751048900463,-0.2502007407407407,-0.18114814814814817,0.24711851851851854
+0.9380843769677465,1967.0,21.0,3139.0,3.0,-71.97435167100694,-0.24941216049382717,-0.17709709876543211,0.24528901234567901
+0.9381468784253364,1988.0,18.0,3134.0,2.0,-71.99119285300925,-0.24862358024691358,-0.17304604938271612,0.2434595061728395
+0.9382093798829264,1999.0,22.0,3148.0,3.0,-72.00803403501158,-0.247835,-0.16899500000000006,0.24163
+0.9382718813405163,1991.0,20.0,3156.0,3.0,-72.02487521701389,-0.24704641975308642,-0.164943950617284,0.2398004938271605
+0.9383343827981063,1996.0,18.0,3153.0,2.0,-72.04171639901621,-0.24625783950617286,-0.16089290123456795,0.237970987654321
+0.9383968842556962,1977.0,18.0,3157.0,6.0,-72.05855758101852,-0.24546925925925928,-0.1568418518518519,0.2361414814814815
+0.9384593857132862,1988.0,16.0,3160.0,3.0,-72.07539876302083,-0.2446806790123457,-0.15279080246913584,0.23431197530864198
+0.9385218871708761,1994.0,20.0,3138.0,4.0,-72.09223994502315,-0.2438920987654321,-0.1487397530864198,0.23248246913580248
+0.9385843886284662,1958.0,18.0,3121.0,3.0,-72.10908112702546,-0.24310351851851852,-0.14468870370370374,0.23065296296296298
+0.9386468900860561,1988.0,18.0,3126.0,2.0,-72.12592230902777,-0.24231493827160494,-0.14063765432098768,0.22882345679012348
+0.9387093915436461,2027.0,19.0,3108.0,2.0,-72.1427634910301,-0.24152635802469136,-0.13658660493827163,0.22699395061728397
+0.9387718930012361,2005.0,16.0,3130.0,2.0,-72.1596046730324,-0.24073777777777777,-0.13253555555555557,0.22516444444444447
+0.938834394458826,1981.0,20.0,3101.0,2.0,-72.17644585503473,-0.2399491975308642,-0.12848450617283957,0.22333493827160494
+0.938896895916416,1968.0,28.0,3103.0,4.0,-72.19328703703704,-0.2391606172839506,-0.12443345679012352,0.22150543209876544
+0.9389593973740059,1976.0,19.0,3100.0,2.0,-72.21012821903935,-0.23837203703703702,-0.12038240740740747,0.21967592592592594
+0.9390218988315959,2036.0,17.0,3102.0,4.0,-72.22696940104167,-0.23758345679012347,-0.11633135802469141,0.21784641975308644
+0.9390844002891858,2003.0,17.0,3099.0,2.0,-72.24381058304398,-0.23679487654320988,-0.11228030864197536,0.21601691358024694
+0.9391469017467758,1986.0,19.0,3104.0,0.0,-72.26065176504629,-0.2360062962962963,-0.1082292592592593,0.21418740740740744
+0.9392094032043657,1991.0,18.0,3099.0,2.0,-72.27749294704861,-0.23521771604938274,-0.10417820987654325,0.2123579012345679
+0.9392719046619558,1947.0,22.0,3099.0,2.0,-72.29433412905092,-0.23442913580246916,-0.1001271604938272,0.2105283950617284
+0.9393344061195457,1967.0,24.0,3125.0,1.0,-72.31117531105325,-0.23364055555555557,-0.09607611111111114,0.2086988888888889
+0.9393969075771357,1953.0,18.0,3085.0,2.0,-72.32801649305556,-0.232851975308642,-0.09202506172839509,0.2068693827160494
+0.9394594090347256,1958.0,17.0,3114.0,2.0,-72.34485767505787,-0.2320633950617284,-0.08797401234567903,0.2050398765432099
+0.9395219104923156,1975.0,19.0,3101.0,8.0,-72.36169885706019,-0.23127481481481482,-0.08392296296296303,0.20321037037037037
+0.9395844119499056,1953.0,28.0,3109.0,2.0,-72.3785400390625,-0.23048623456790124,-0.07987191358024698,0.20138086419753087
+0.9396469134074955,1970.0,19.0,3118.0,3.0,-72.39538122106481,-0.22969765432098765,-0.07582086419753092,0.19955135802469137
+0.9397094148650855,1971.0,16.0,3128.0,2.0,-72.41222240306713,-0.22890907407407407,-0.07176981481481487,0.19772185185185187
+0.9397719163226754,1972.0,18.0,3146.0,3.0,-72.42906358506944,-0.2281204938271605,-0.06771876543209882,0.19589234567901237
+0.9398344177802654,1981.0,21.0,3153.0,2.0,-72.44590476707175,-0.2273319135802469,-0.06366771604938276,0.19406283950617287
+0.9398969192378553,1989.0,17.0,3147.0,2.0,-72.46274594907408,-0.22654333333333335,-0.05961666666666671,0.19223333333333334
+0.9399594206954454,1988.0,16.0,3154.0,1.0,-72.47958713107639,-0.22575475308641976,-0.05556561728395065,0.19040382716049384
+0.9400219221530353,2039.0,16.0,3163.0,3.0,-72.49642831307871,-0.22496617283950618,-0.0515145679012346,0.18857432098765434
+0.9400844236106253,2012.0,17.0,3154.0,2.0,-72.51326949508102,-0.2241775925925926,-0.047463518518518544,0.18674481481481484
+0.9401469250682152,2002.0,18.0,3146.0,2.0,-72.53011067708333,-0.22338901234567904,-0.04341246913580249,0.18491530864197533
+0.9402094265258052,2001.0,18.0,3151.0,2.0,-72.54695185908565,-0.22260043209876546,-0.03936141975308649,0.18308580246913583
+0.9402719279833951,1963.0,26.0,3169.0,2.0,-72.56379304108796,-0.22181185185185187,-0.035310370370370436,0.1812562962962963
+0.9403344294409851,1993.0,21.0,3184.0,4.0,-72.58063422309027,-0.2210232716049383,-0.03125932098765438,0.1794267901234568
+0.940396930898575,1986.0,16.0,3162.0,2.0,-72.5974754050926,-0.2202346913580247,-0.027208271604938328,0.1775972839506173
+0.940459432356165,1982.0,17.0,3202.0,2.0,-72.6143165870949,-0.21944611111111112,-0.023157222222222273,0.1757677777777778
+0.940521933813755,1992.0,17.0,3224.0,2.0,-72.63115776909723,-0.21865753086419754,-0.01910617283950622,0.1739382716049383
+0.9405844352713449,1982.0,21.0,3217.0,2.0,-72.64799895109954,-0.21786895061728395,-0.015055123456790165,0.1721087654320988
+0.940646936728935,1989.0,16.0,3210.0,2.0,-72.66484013310185,-0.21708037037037037,-0.01100407407407411,0.17027925925925927
+0.9407094381865249,2029.0,14.0,3189.0,2.0,-72.68168131510417,-0.21629179012345678,-0.006953024691358056,0.16844975308641977
+0.9407719396441149,1997.0,17.0,3196.0,3.0,-72.69852249710648,-0.2155032098765432,-0.002901975308642002,0.16662024691358027
+0.9408344411017048,1998.0,16.0,3207.0,4.0,-72.71536367910879,-0.21471462962962964,0.0011490740740739969,0.16479074074074077
+0.9408969425592948,2018.0,16.0,3200.0,1.0,-72.73220486111111,-0.21392604938271606,0.005200123456790051,0.16296123456790126
+0.9409594440168847,2000.0,16.0,3194.0,3.0,-72.74904604311342,-0.21313746913580248,0.009251172839506105,0.16113172839506176
+0.9410219454744747,2050.0,12.0,3198.0,2.0,-72.76588722511575,-0.2123488888888889,0.01330222222222216,0.15930222222222223
+0.9410844469320646,2017.0,17.0,3190.0,2.0,-72.78272840711806,-0.21156030864197534,0.017353271604938214,0.15747271604938273
+0.9411469483896546,2004.0,18.0,3180.0,2.0,-72.79956958912037,-0.21077172839506175,0.02140432098765427,0.15564320987654323
+0.9412094498472445,2004.0,17.0,3166.0,2.0,-72.81641077112269,-0.20998314814814817,0.025455370370370323,0.15381370370370373
+0.9412719513048345,1967.0,22.0,3170.0,2.0,-72.833251953125,-0.20919456790123458,0.029506419753086377,0.15198419753086423
+0.9413344527624246,2000.0,20.0,3187.0,4.0,-72.85009313512731,-0.208405987654321,0.03355746913580243,0.1501546913580247
+0.9413969542200145,2036.0,16.0,3174.0,2.0,-72.86693431712963,-0.20761740740740742,0.037608518518518486,0.1483251851851852
+0.9414594556776045,2034.0,17.0,3202.0,2.0,-72.88377549913194,-0.20682882716049383,0.04165956790123454,0.1464956790123457
+0.9415219571351944,2019.0,18.0,3219.0,3.0,-72.90061668113425,-0.20604024691358025,0.045710617283950594,0.1446661728395062
+0.9415844585927844,2054.0,14.0,3192.0,2.0,-72.91745786313658,-0.20525166666666667,0.04976166666666665,0.1428366666666667
+0.9416469600503743,2029.0,16.0,3180.0,2.0,-72.93429904513889,-0.20446308641975308,0.0538127160493827,0.1410071604938272
+0.9417094615079643,2025.0,19.0,3191.0,2.0,-72.95114022714121,-0.2036745061728395,0.05786376543209876,0.13917765432098766
+0.9417719629655542,2014.0,16.0,3173.0,2.0,-72.96798140914352,-0.20288592592592594,0.06191481481481481,0.13734814814814816
+0.9418344644231442,2014.0,20.0,3166.0,4.0,-72.98482259114583,-0.20209734567901236,0.06596586419753075,0.13551864197530866
+0.9418969658807341,2014.0,16.0,3186.0,2.0,-73.00166377314815,-0.20130876543209877,0.07001691358024681,0.13368913580246916
+0.9419594673383241,2022.0,17.0,3180.0,2.0,-73.01850495515046,-0.20052018518518522,0.07406796296296286,0.13185962962962966
+0.942021968795914,2027.0,14.0,3187.0,2.0,-73.03534613715277,-0.19973160493827163,0.07811901234567892,0.13003012345679016
+0.9420844702535041,2024.0,18.0,3195.0,2.0,-73.0521873191551,-0.19894302469135805,0.08217006172839497,0.12820061728395066
+0.942146971711094,2033.0,16.0,3190.0,2.0,-73.0690285011574,-0.19815444444444447,0.08622111111111103,0.12637111111111116
+0.942209473168684,2022.0,17.0,3166.0,2.0,-73.08586968315973,-0.19736586419753088,0.09027216049382708,0.12454160493827166
+0.942271974626274,1993.0,18.0,3165.0,3.0,-73.10271086516204,-0.1965772839506173,0.09432320987654313,0.1227120987654321
+0.9423344760838639,2012.0,16.0,3167.0,2.0,-73.11955204716435,-0.19578870370370371,0.09837425925925919,0.1208825925925926
+0.9423969775414539,2013.0,18.0,3147.0,4.0,-73.13639322916667,-0.19500012345679013,0.10242530864197524,0.1190530864197531
+0.9424594789990438,2010.0,16.0,3160.0,2.0,-73.15323441116898,-0.19421154320987655,0.1064763580246913,0.1172235802469136
+0.9425219804566338,2024.0,17.0,3153.0,2.0,-73.17007559317129,-0.19342296296296296,0.11052740740740735,0.1153940740740741
+0.9425844819142237,2016.0,16.0,3156.0,2.0,-73.18691677517361,-0.19263438271604938,0.1145784567901234,0.11356456790123459
+0.9426469833718137,2023.0,18.0,3156.0,2.0,-73.20375795717592,-0.19184580246913582,0.11862950617283946,0.11173506172839509
+0.9427094848294036,2079.0,20.0,3165.0,5.0,-73.22059913917825,-0.19105722222222224,0.12268055555555551,0.10990555555555559
+0.9427719862869937,2031.0,16.0,3167.0,2.0,-73.23744032118056,-0.19026864197530866,0.12673160493827157,0.10807604938271609
+0.9428344877445836,2032.0,16.0,3190.0,4.0,-73.25428150318287,-0.18948006172839507,0.13078265432098762,0.10624654320987659
+0.9428969892021736,2059.0,14.0,3167.0,2.0,-73.27112268518519,-0.18869148148148152,0.13483370370370368,0.10441703703703709
+0.9429594906597635,2039.0,16.0,3174.0,2.0,-73.2879638671875,-0.18790290123456793,0.13888475308641973,0.10258753086419758
+0.9430219921173535,2069.0,16.0,3189.0,0.0,-73.30480504918981,-0.18711432098765435,0.1429358024691358,0.10075802469135803
+0.9430844935749434,2034.0,16.0,3182.0,2.0,-73.32164623119213,-0.18632574074074076,0.14698685185185184,0.09892851851851853
+0.9431469950325334,2025.0,16.0,3174.0,2.0,-73.33848741319444,-0.18553716049382718,0.15103790123456778,0.09709901234567903
+0.9432094964901234,2021.0,18.0,3164.0,6.0,-73.35532859519675,-0.1847485802469136,0.15508895061728384,0.09526950617283952
+0.9432525951557093,2012.0,17.0,3161.5,4.0,-73.37216977719908,-0.18396,0.15913999999999998,0.09344
+0.9432719979477133,2003.0,16.0,3159.0,2.0,-73.38901095920139,-0.18183717791411044,0.15737993865030672,0.09195760736196319
+0.9433344994053033,2014.0,18.0,3166.0,4.0,-73.40585214120371,-0.17971435582822087,0.15561987730061347,0.09047521472392638
+0.9433970008628932,2035.0,14.0,3139.0,2.0,-73.42269332320602,-0.1775915337423313,0.15385981595092021,0.08899282208588957
+0.9434595023204833,2020.0,16.0,3150.0,2.0,-73.43953450520833,-0.17546871165644173,0.15209975460122696,0.08751042944785276
+0.9435220037780732,2025.0,16.0,3144.0,2.0,-73.45637568721065,-0.17334588957055216,0.1503396932515337,0.08602803680981595
+0.9435845052356632,2039.0,11.0,3141.0,2.0,-73.47321686921296,-0.1712230674846626,0.14857963190184048,0.08454564417177914
+0.9436470066932531,2031.0,16.0,3153.0,2.0,-73.49005805121527,-0.16910024539877302,0.14681957055214723,0.08306325153374233
+0.9437095081508431,2082.0,17.0,3149.0,4.0,-73.5068992332176,-0.16697742331288346,0.14505950920245397,0.08158085889570552
+0.943772009608433,2042.0,14.0,3149.0,2.0,-73.5237404152199,-0.16485460122699389,0.14329944785276072,0.08009846625766871
+0.943834511066023,2034.0,16.0,3168.0,4.0,-73.54058159722223,-0.16273177914110432,0.14153938650306747,0.0786160736196319
+0.9438970125236129,2061.0,16.0,3138.0,2.0,-73.55742277922454,-0.16060895705521475,0.1397793251533742,0.07713368098159509
+0.9439595139812029,2039.0,16.0,3130.0,3.0,-73.57426396122685,-0.15848613496932518,0.13801926380368096,0.07565128834355828
+0.9440220154387929,2082.0,16.0,3125.0,2.0,-73.59110514322917,-0.1563633128834356,0.1362592024539877,0.07416889570552147
+0.9440845168963828,2048.0,16.0,3122.0,2.0,-73.60794632523148,-0.15424049079754604,0.13449914110429445,0.07268650306748466
+0.9441470183539729,2030.0,16.0,3114.0,3.0,-73.62478750723379,-0.15211766871165644,0.1327390797546012,0.07120411042944785
+0.9442095198115628,2020.0,16.0,3114.0,2.0,-73.64162868923611,-0.1499948466257669,0.13097901840490794,0.06972171779141104
+0.9442720212691528,2024.0,14.0,3117.0,2.0,-73.65846987123842,-0.1478720245398773,0.1292189570552147,0.06823932515337423
+0.9443345227267427,2013.0,17.0,3132.0,3.0,-73.67531105324075,-0.14574920245398776,0.12745889570552144,0.06675693251533742
+0.9443970241843327,2042.0,17.0,3147.0,2.0,-73.69215223524306,-0.14362638036809816,0.1256988343558282,0.06527453987730061
+0.9444595256419226,2041.0,17.0,3126.0,2.0,-73.70899341724537,-0.14150355828220862,0.12393877300613496,0.0637921472392638
+0.9445220270995126,2023.0,14.0,3133.0,2.0,-73.72583459924769,-0.13938073619631902,0.1221787116564417,0.062309754601226994
+0.9445845285571025,2030.0,14.0,3124.0,2.0,-73.74267578125,-0.13725791411042945,0.12041865030674845,0.060827361963190184
+0.9446470300146925,2034.0,16.0,3122.0,2.0,-73.75951696325231,-0.13513509202453988,0.1186585889570552,0.059344969325153374
+0.9447095314722824,2008.0,18.0,3114.0,2.0,-73.77635814525463,-0.1330122699386503,0.11689852760736194,0.057862576687116564
+0.9447720329298724,2029.0,17.0,3109.0,2.0,-73.79319932725694,-0.13088944785276074,0.11513846625766869,0.056380184049079754
+0.9448345343874623,2034.0,14.0,3127.0,2.0,-73.81004050925925,-0.12876662576687117,0.11337840490797543,0.054897791411042944
+0.9448970358450524,2048.0,14.0,3116.0,3.0,-73.82688169126158,-0.1266438036809816,0.11161834355828218,0.053415398773006134
+0.9449595373026424,2043.0,18.0,3115.0,4.0,-73.84372287326389,-0.12452098159509203,0.10985828220858894,0.051933006134969324
+0.9450220387602323,2035.0,18.0,3122.0,3.0,-73.86056405526621,-0.12239815950920246,0.10809822085889569,0.050450613496932514
+0.9450845402178223,2042.0,17.0,3118.0,2.0,-73.87740523726852,-0.1202753374233129,0.10633815950920243,0.048968220858895704
+0.9451470416754122,2032.0,16.0,3112.0,2.0,-73.89424641927083,-0.11815251533742333,0.10457809815950919,0.047485828220858894
+0.9452095431330022,2029.0,16.0,3110.0,2.0,-73.91108760127315,-0.11602969325153376,0.10281803680981594,0.046003435582822085
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+0.9829604235173395,1979.0,26.0,3183.0,2.0,-83.77821180555556,-0.002257592592592561,-3.160782839506173,-0.5710312345679012
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+0.9839604468387789,1918.0,17.0,3187.0,2.0,-84.04721860532408,-0.06670766871165644,-3.214915521472393,-0.5382966257668711
+0.9840229482963688,1935.0,19.0,3185.0,2.0,-84.06304253472223,-0.0715534355828221,-3.212506073619632,-0.5348212883435582
+0.9840854497539588,1944.0,19.0,3219.0,3.0,-84.07886646412037,-0.07639920245398774,-3.2100966257668713,-0.5313459509202454
+0.9841479512115487,1959.0,24.0,3216.0,3.0,-84.09469039351852,-0.08124496932515338,-3.2076871779141105,-0.5278706134969324
+0.9842104526691388,1966.0,19.0,3230.0,2.0,-84.11051432291667,-0.08609073619631903,-3.2052777300613498,-0.5243952760736196
+0.9842729541267287,1915.0,17.0,3184.0,2.0,-84.12633825231481,-0.09093650306748467,-3.202868282208589,-0.5209199386503067
+0.9843354555843187,1919.0,16.0,3201.0,3.0,-84.14216218171296,-0.09578226993865031,-3.2004588343558282,-0.5174446012269938
+0.9843979570419086,1938.0,18.0,3199.0,2.0,-84.15798611111111,-0.10062803680981595,-3.1980493865030675,-0.5139692638036809
+0.9844604584994986,1917.0,26.0,3197.0,3.0,-84.17381004050925,-0.1054738036809816,-3.1956399386503067,-0.5104939263803681
+0.9845229599570886,1937.0,24.0,3207.0,4.0,-84.1896339699074,-0.11031957055214725,-3.193230490797546,-0.5070185889570552
+0.9845854614146785,1985.0,15.0,3204.0,2.0,-84.20545789930556,-0.11516533742331289,-3.190821042944785,-0.5035432515337422
+0.9846479628722685,1950.0,14.0,3206.0,3.0,-84.22128182870371,-0.12001110429447853,-3.1884115950920244,-0.5000679141104294
+0.9847104643298584,1941.0,14.0,3221.0,2.0,-84.23710575810185,-0.12485687116564419,-3.1860021472392637,-0.49659257668711654
+0.9847729657874484,1891.0,20.0,3183.0,2.0,-84.2529296875,-0.12970263803680981,-3.183592699386503,-0.49311723926380363
+0.9848354672450383,1945.0,16.0,3267.0,2.0,-84.26875361689815,-0.13454840490797546,-3.181183251533742,-0.4896419018404907
+0.9848979687026284,1929.0,16.0,3253.0,4.0,-84.28457754629629,-0.1393941717791411,-3.1787738036809814,-0.48616656441717787
+0.9849604701602183,1912.0,16.0,3193.0,2.0,-84.30040147569444,-0.14423993865030674,-3.1763643558282206,-0.482691226993865
+0.9850229716178083,1949.0,18.0,3208.0,5.0,-84.3162254050926,-0.14908570552147238,-3.1739549079754603,-0.4792158895705521
+0.9850854730753982,1962.0,16.0,3262.0,2.0,-84.33204933449075,-0.15393147239263805,-3.1715454601226996,-0.4757405521472392
+0.9851479745329882,1966.0,12.0,3226.0,3.0,-84.34787326388889,-0.1587772392638037,-3.169136012269939,-0.47226521472392635
+0.9852104759905781,1976.0,16.0,3237.0,2.0,-84.36369719328704,-0.16362300613496933,-3.166726564417178,-0.46878987730061344
+0.9852729774481681,1958.0,13.0,3242.0,3.0,-84.37952112268519,-0.16846877300613497,-3.1643171165644173,-0.46531453987730054
+0.9853354789057581,1965.0,14.0,3225.0,3.0,-84.39534505208333,-0.1733145398773006,-3.1619076687116565,-0.4618392024539877
+0.985397980363348,1972.0,16.0,3219.0,3.0,-84.41116898148148,-0.17816030674846625,-3.1594982208588958,-0.45836386503067483
+0.985460481820938,1947.0,17.0,3201.0,2.0,-84.42699291087963,-0.1830060736196319,-3.157088773006135,-0.4548885276073619
+0.9855229832785279,1973.0,20.0,3179.0,4.0,-84.44281684027777,-0.18785184049079753,-3.1546793251533742,-0.451413190184049
+0.985585484736118,2020.0,16.0,3226.0,2.0,-84.45864076967592,-0.19269760736196317,-3.1522698773006135,-0.44793785276073617
+0.9856479861937079,1982.0,17.0,3218.0,3.0,-84.47446469907408,-0.19754337423312884,-3.1498604294478527,-0.44446251533742326
+0.9857104876512979,1944.0,16.0,3208.0,2.0,-84.49028862847223,-0.20238914110429448,-3.147450981595092,-0.44098717791411035
+0.9857729891088878,1947.0,16.0,3233.0,2.0,-84.50611255787037,-0.20723490797546013,-3.145041533742331,-0.4375118404907975
+0.9858354905664778,1960.0,16.0,3240.0,2.0,-84.52193648726852,-0.21208067484662577,-3.1426320858895704,-0.43403650306748465
+0.9858979920240677,2014.0,16.0,3242.0,2.0,-84.53776041666667,-0.2169264417177914,-3.1402226380368097,-0.43056116564417174
+0.9859604934816577,1977.0,16.0,3215.0,2.0,-84.55358434606481,-0.22177220858895705,-3.137813190184049,-0.42708582822085883
+0.9860229949392476,1994.0,14.0,3253.0,2.0,-84.56940827546296,-0.2266179754601227,-3.135403742331288,-0.423610490797546
+0.9860854963968376,1986.0,17.0,3283.0,2.0,-84.58523220486111,-0.23146374233128836,-3.1329942944785274,-0.4201351533742331
+0.9861479978544275,2015.0,17.0,3241.0,2.0,-84.60105613425925,-0.236309509202454,-3.1305848466257666,-0.41665981595092016
+0.9862104993120175,1976.0,18.0,3243.0,1.0,-84.6168800636574,-0.24115527607361964,-3.1281753987730063,-0.4131844785276073
+0.9862730007696076,1945.0,16.0,3238.0,3.0,-84.63270399305556,-0.24600104294478528,-3.1257659509202456,-0.40970914110429446
+0.9863355022271975,1962.0,16.0,3243.0,2.0,-84.64852792245371,-0.2508468098159509,-3.123356503067485,-0.40623380368098155
+0.9863980036847875,1974.0,16.0,3242.0,1.0,-84.66435185185185,-0.2556925766871166,-3.120947055214724,-0.40275846625766865
+0.9864605051423774,1923.0,20.0,3226.0,6.0,-84.68017578125,-0.2605383435582822,-3.1185376073619633,-0.3992831288343558
+0.9865230065999674,1959.0,17.0,3243.0,2.0,-84.69599971064815,-0.2653841104294479,-3.1161281595092025,-0.39580779141104294
+0.9865855080575573,1939.0,17.0,3227.0,2.0,-84.71182364004629,-0.2702298773006135,-3.1137187116564418,-0.39233245398773003
+0.9866480095151473,1951.0,17.0,3241.0,6.0,-84.72764756944444,-0.27507564417177915,-3.111309263803681,-0.3888571165644171
+0.9867105109727372,1969.0,17.0,3223.0,2.0,-84.7434714988426,-0.27992141104294477,-3.1088998159509202,-0.3853817791411043
+0.9867730124303272,1924.0,21.0,3210.0,4.0,-84.75929542824073,-0.28476717791411044,-3.1064903680981595,-0.38190644171779137
+0.9868355138879171,1959.0,18.0,3243.0,2.0,-84.77511935763889,-0.2896129447852761,-3.1040809202453987,-0.37843110429447846
+0.9868980153455071,1971.0,13.0,3194.0,3.0,-84.79094328703704,-0.2944587116564417,-3.101671472392638,-0.3749557668711656
+0.986960516803097,1989.0,16.0,3247.0,2.0,-84.80676721643519,-0.2993044785276074,-3.099262024539877,-0.37148042944785276
+0.9870230182606871,1973.0,16.0,3274.0,2.0,-84.82259114583333,-0.304150245398773,-3.0968525766871164,-0.36800509202453985
+0.9870855197182771,1959.0,16.0,3217.0,2.0,-84.83841507523148,-0.30899601226993867,-3.0944431288343557,-0.36452975460122694
+0.987148021175867,1998.0,19.0,3253.0,6.0,-84.85423900462963,-0.3138417791411043,-3.092033680981595,-0.3610544171779141
+0.987210522633457,1962.0,19.0,3248.0,2.0,-84.87006293402777,-0.31868754601226995,-3.089624233128834,-0.3575790797546012
+0.9872730240910469,1996.0,18.0,3227.0,4.0,-84.88588686342592,-0.32353331288343556,-3.087214785276074,-0.3541037423312883
+0.9873355255486369,1987.0,18.0,3258.0,2.0,-84.90171079282408,-0.32837907975460123,-3.084805337423313,-0.3506284049079754
+0.9873980270062268,1954.0,16.0,3240.0,2.0,-84.91753472222223,-0.3332248466257669,-3.0823958895705523,-0.34715306748466257
+0.9874605284638168,2002.0,14.0,3263.0,2.0,-84.93335865162037,-0.3380706134969325,-3.0799864417177916,-0.34367773006134966
+0.9875230299214067,1995.0,16.0,3260.0,2.0,-84.94918258101852,-0.3429163803680982,-3.077576993865031,-0.34020239263803675
+0.9875855313789967,2018.0,17.0,3267.0,2.0,-84.96500651041667,-0.3477621472392638,-3.07516754601227,-0.3367270552147239
+0.9876480328365866,1983.0,18.0,3233.0,2.0,-84.98083043981481,-0.35260791411042947,-3.0727580981595093,-0.333251717791411
+0.9877105342941767,1993.0,16.0,3263.0,3.0,-84.99665436921296,-0.3574536809815951,-3.0703486503067485,-0.3297763803680981
+0.9877730357517666,1986.0,16.0,3221.0,2.0,-85.01247829861111,-0.36229944785276075,-3.0679392024539878,-0.32630104294478524
+0.9878355372093566,1965.0,14.0,3205.0,2.0,-85.02830222800925,-0.36714521472392636,-3.065529754601227,-0.3228257055214724
+0.9878980386669465,2003.0,19.0,3193.0,4.0,-85.0441261574074,-0.37199098159509203,-3.0631203067484662,-0.3193503680981595
+0.9879605401245365,2005.0,16.0,3247.0,2.0,-85.05995008680556,-0.3768367484662577,-3.0607108588957055,-0.31587503067484657
+0.9880230415821265,1994.0,17.0,3262.0,2.0,-85.07577401620371,-0.3816825153374233,-3.0583014110429447,-0.3123996932515337
+0.9880855430397164,1995.0,16.0,3230.0,3.0,-85.09159794560185,-0.386528282208589,-3.055891963190184,-0.3089243558282208
+0.9881480444973064,2010.0,16.0,3226.0,2.0,-85.107421875,-0.3913740490797546,-3.053482515337423,-0.30544901840490796
+0.9882105459548963,1966.0,17.0,3205.0,2.0,-85.12324580439815,-0.39621981595092026,-3.0510730674846624,-0.30197368098159505
+0.9882730474124863,2029.0,16.0,3224.0,2.0,-85.13906973379629,-0.4010655828220859,-3.0486636196319017,-0.2984983435582822
+0.9883355488700762,2006.0,16.0,3236.0,4.0,-85.15489366319444,-0.40591134969325154,-3.046254171779141,-0.2950230061349693
+0.9883980503276663,2018.0,16.0,3250.0,3.0,-85.1707175925926,-0.4107571165644172,-3.04384472392638,-0.2915476687116564
+0.9884605517852562,2035.0,14.0,3288.0,3.0,-85.18654152199073,-0.4156028834355828,-3.04143527607362,-0.28807233128834353
+0.9885230532428462,2016.0,16.0,3262.0,2.0,-85.20236545138889,-0.4204486503067485,-3.039025828220859,-0.2845969938650306
+0.9885855547004361,1956.0,20.0,3230.0,2.0,-85.21818938078704,-0.4252944171779141,-3.0366163803680983,-0.28112165644171777
+0.9886480561580261,1991.0,21.0,3218.0,2.0,-85.23401331018519,-0.4301401840490798,-3.0342069325153376,-0.27764631901840486
+0.988710557615616,1993.0,13.0,3253.0,2.0,-85.24983723958333,-0.4349859509202454,-3.031797484662577,-0.274170981595092
+0.988773059073206,1988.0,18.0,3258.0,5.0,-85.26566116898148,-0.43983171779141106,-3.029388036809816,-0.2706956441717791
+0.988835560530796,1977.0,16.0,3226.0,2.0,-85.28148509837963,-0.4446774846625767,-3.0269785889570553,-0.2672203067484662
+0.9888980619883859,2006.0,20.0,3254.0,4.0,-85.29730902777777,-0.44952325153374234,-3.0245691411042945,-0.26374496932515334
+0.9889605634459759,2002.0,18.0,3270.0,2.0,-85.31313295717592,-0.454369018404908,-3.0221596932515338,-0.26026963190184044
+0.9890230649035658,2024.0,16.0,3238.0,2.0,-85.32895688657408,-0.4592147852760736,-3.019750245398773,-0.2567942944785276
+0.9890855663611559,1978.0,16.0,3224.0,2.0,-85.34478081597223,-0.4640605521472393,-3.0173407975460123,-0.2533189570552147
+0.9891480678187458,2024.0,16.0,3282.0,2.0,-85.36060474537037,-0.4689063190184049,-3.0149313496932515,-0.24984361963190183
+0.9892105692763358,1994.0,18.0,3248.0,2.0,-85.37642867476852,-0.4737520858895706,-3.0125219018404907,-0.24636828220858892
+0.9892730707339257,1968.0,20.0,3200.0,4.0,-85.39225260416667,-0.4785978527607362,-3.01011245398773,-0.24289294478527607
+0.9893355721915157,1971.0,16.0,3185.0,2.0,-85.40807653356481,-0.48344361963190186,-3.007703006134969,-0.23941760736196316
+0.9893980736491056,2002.0,19.0,3244.0,2.0,-85.42390046296296,-0.4882893865030675,-3.0052935582822085,-0.23594226993865025
+0.9894605751066956,1986.0,22.0,3241.0,2.0,-85.43972439236111,-0.49313515337423314,-3.0028841104294477,-0.2324669325153374
+0.9895230765642855,1988.0,18.0,3263.0,2.0,-85.45554832175925,-0.4979809202453988,-3.0004746625766874,-0.2289915950920245
+0.9895855780218755,2033.0,18.0,3294.0,2.0,-85.4713722511574,-0.5028266871165644,-2.9980652147239266,-0.22551625766871164
+0.9896480794794654,1990.0,18.0,3278.0,2.0,-85.48719618055556,-0.5076724539877301,-2.995655766871166,-0.22204092024539873
+0.9897105809370554,1961.0,18.0,3254.0,2.0,-85.50302010995371,-0.5125182208588958,-2.993246319018405,-0.21856558282208588
+0.9897730823946455,2009.0,16.0,3253.0,4.0,-85.51884403935185,-0.5173639877300614,-2.9908368711656443,-0.21509024539877297
+0.9898355838522354,1980.0,16.0,3236.0,2.0,-85.53466796875,-0.522209754601227,-2.9884274233128836,-0.21161490797546012
+0.9898980853098254,2006.0,18.0,3250.0,4.0,-85.55049189814815,-0.5270555214723927,-2.986017975460123,-0.2081395705521472
+0.9899605867674153,1970.0,19.0,3227.0,2.0,-85.56631582754629,-0.5319012883435583,-2.983608527607362,-0.2046642331288343
+0.9900230882250053,1951.0,18.0,3228.0,3.0,-85.58213975694444,-0.536747055214724,-2.9811990797546013,-0.20118889570552145
+0.9900855896825952,1967.0,16.0,3241.0,2.0,-85.5979636863426,-0.5415928220858895,-2.9787896319018405,-0.19771355828220855
+0.9901480911401852,1977.0,17.0,3250.0,2.0,-85.61378761574073,-0.5464385889570552,-2.97638018404908,-0.1942382208588957
+0.9902105925977751,1968.0,21.0,3249.0,2.0,-85.62961154513889,-0.5512843558282209,-2.973970736196319,-0.1907628834355828
+0.9902730940553651,1966.0,15.0,3234.0,3.0,-85.64543547453704,-0.5561301226993866,-2.9715612883435583,-0.18728754601226993
+0.990335595512955,1965.0,18.0,3251.0,2.0,-85.66125940393519,-0.5609758895705522,-2.9691518404907975,-0.18381220858895703
+0.990398096970545,1976.0,17.0,3252.0,3.0,-85.67708333333333,-0.5658216564417178,-2.9667423926380367,-0.18033687116564412
+0.9904605984281349,1979.0,20.0,3259.0,2.0,-85.69290726273148,-0.5706674233128834,-2.964332944785276,-0.17686153374233127
+0.990523099885725,1978.0,16.0,3265.0,2.0,-85.70873119212963,-0.5755131901840491,-2.961923496932515,-0.17338619631901836
+0.9905856013433149,2021.0,14.0,3256.0,2.0,-85.72455512152777,-0.5803589570552148,-2.959514049079755,-0.1699108588957055
+0.9906481028009049,1988.0,16.0,3253.0,2.0,-85.74037905092592,-0.5852047239263803,-2.9571046012269937,-0.1664355214723926
+0.9907106042584949,1987.0,12.0,3265.0,5.0,-85.75620298032408,-0.590050490797546,-2.9546951533742334,-0.16296018404907975
+0.9907731057160848,2011.0,18.0,3261.0,4.0,-85.77202690972223,-0.5948962576687117,-2.9522857055214726,-0.15948484662576684
+0.9908356071736748,1993.0,18.0,3255.0,2.0,-85.78785083912037,-0.5997420245398773,-2.949876257668712,-0.15600950920245393
+0.9908981086312647,2038.0,13.0,3262.0,2.0,-85.80367476851852,-0.604587791411043,-2.947466809815951,-0.15253417177914108
+0.9909606100888547,1987.0,19.0,3274.0,2.0,-85.81949869791667,-0.6094335582822086,-2.9450573619631903,-0.14905883435582817
+0.9910231115464446,1961.0,13.0,3263.0,2.0,-85.83532262731481,-0.6142793251533742,-2.9426479141104296,-0.14558349693251532
+0.9910856130040346,1987.0,18.0,3262.0,2.0,-85.85114655671296,-0.6191250920245399,-2.940238466257669,-0.14210815950920241
+0.9911481144616245,1969.0,16.0,3262.0,2.0,-85.86697048611111,-0.6239708588957056,-2.937829018404908,-0.13863282208588956
+0.9912106159192146,1976.0,18.0,3256.0,2.0,-85.88279441550925,-0.6288166257668711,-2.9354195705521473,-0.13515748466257665
+0.9912731173768045,2009.0,16.0,3234.0,4.0,-85.8986183449074,-0.6336623926380368,-2.9330101226993865,-0.1316821472392638
+0.9913356188343945,2001.0,18.0,3246.0,2.0,-85.91444227430556,-0.6385081595092025,-2.930600674846626,-0.1282068098159509
+0.9913981202919844,1988.0,17.0,3278.0,2.0,-85.93026620370371,-0.6433539263803681,-2.928191226993865,-0.12473147239263799
+0.9914606217495744,2014.0,16.0,3251.0,2.0,-85.94609013310185,-0.6481996932515338,-2.9257817791411043,-0.12125613496932514
+0.9915032679738562,2003.5,16.5,3246.0,2.0,-85.9619140625,-0.6530454601226994,-2.9233723312883435,-0.11778079754601223
+0.9915231232071644,1993.0,17.0,3241.0,2.0,-85.97759281823394,-0.657891226993865,-2.9209628834355827,-0.11430546012269938
+0.9915856246647543,2013.0,18.0,3261.0,2.0,-85.99327157396789,-0.6627369938650307,-2.918553435582822,-0.11083012269938647
+0.9916481261223443,1995.0,19.0,3265.0,2.0,-86.00895032970183,-0.6675827607361964,-2.9161439877300612,-0.10735478527607362
+0.9917106275799342,1980.0,16.0,3286.0,3.0,-86.02462908543578,-0.6724285276073619,-2.913734539877301,-0.10387944785276071
+0.9917731290375242,2000.0,14.0,3273.0,3.0,-86.04030784116972,-0.6772742944785276,-2.91132509202454,-0.10040411042944786
+0.9918356304951141,1981.0,16.0,3265.0,4.0,-86.05598659690367,-0.6821200613496933,-2.9089156441717794,-0.09692877300613495
+0.9918981319527042,1981.0,19.0,3273.0,2.0,-86.07166535263761,-0.6869658282208589,-2.9065061963190186,-0.09345343558282204
+0.9919606334102941,1977.0,18.0,3259.0,2.0,-86.08734410837155,-0.6918115950920246,-2.904096748466258,-0.08997809815950919
+0.9920231348678841,1957.0,16.0,3269.0,2.0,-86.1030228641055,-0.6966573619631902,-2.901687300613497,-0.08650276073619628
+0.992085636325474,1962.0,17.0,3249.0,4.0,-86.11870161983946,-0.7015031288343558,-2.8992778527607364,-0.08302742331288343
+0.992148137783064,1941.0,22.0,3231.0,3.0,-86.1343803755734,-0.7063488957055215,-2.8968684049079756,-0.07955208588957052
+0.9922106392406539,1955.0,16.0,3236.0,3.0,-86.15005913130734,-0.7111946625766872,-2.894458957055215,-0.07607674846625767
+0.9922731406982439,1924.0,21.0,3251.0,2.0,-86.16573788704129,-0.7160404294478527,-2.892049509202454,-0.07260141104294482
+0.9923356421558338,1943.0,19.0,3248.0,2.0,-86.18141664277523,-0.7208861963190184,-2.8896400613496933,-0.06912607361963186
+0.9923981436134238,1946.0,21.0,3229.0,2.0,-86.19709539850918,-0.7257319631901841,-2.8872306134969326,-0.065650736196319
+0.9924606450710138,1946.0,22.0,3251.0,2.0,-86.21277415424312,-0.7305777300613497,-2.884821165644172,-0.06217539877300615
+0.9925231465286037,1960.0,20.0,3251.0,2.0,-86.22845290997707,-0.7354234969325154,-2.882411717791411,-0.05870006134969319
+0.9925856479861938,1959.0,22.0,3248.0,3.0,-86.24413166571101,-0.740269263803681,-2.8800022699386503,-0.05522472392638034
+0.9926481494437837,1961.0,17.0,3248.0,2.0,-86.25981042144495,-0.7451150306748466,-2.8775928220858895,-0.051749386503067485
+0.9927106509013737,1998.0,16.0,3237.0,2.0,-86.2754891771789,-0.7499607975460123,-2.8751833742331288,-0.04827404907975463
+0.9927731523589636,1985.0,16.0,3250.0,5.0,-86.29116793291284,-0.754806564417178,-2.8727739263803684,-0.04479871165644167
+0.9928356538165536,1982.0,16.0,3236.0,2.0,-86.30684668864679,-0.7596523312883436,-2.8703644785276072,-0.04132337423312882
+0.9928981552741435,1966.0,19.0,3246.0,2.0,-86.32252544438073,-0.7644980981595092,-2.867955030674847,-0.037848036809815966
+0.9929606567317335,1984.0,17.0,3242.0,2.0,-86.33820420011467,-0.7693438650306749,-2.865545582822086,-0.034372699386503
+0.9930231581893234,1958.0,17.0,3236.0,3.0,-86.35388295584862,-0.7741896319018405,-2.8631361349693254,-0.03089736196319015
+0.9930856596469134,1982.0,17.0,3243.0,2.0,-86.36956171158256,-0.7790353987730062,-2.8607266871165646,-0.0274220245398773
+0.9931481611045033,1959.0,18.0,3239.0,2.0,-86.3852404673165,-0.7838811656441718,-2.858317239263804,-0.023946687116564447
+0.9932106625620933,1986.0,18.0,3237.0,2.0,-86.40091922305047,-0.7887269325153374,-2.855907791411043,-0.020471349693251484
+0.9932731640196834,2034.0,18.0,3233.0,4.0,-86.41659797878441,-0.7935726993865031,-2.8534983435582824,-0.016996012269938632
+0.9933356654772733,1998.0,16.0,3235.0,2.0,-86.43227673451835,-0.7984184662576688,-2.8510888957055216,-0.01352067484662578
+0.9933981669348633,1988.0,14.0,3259.0,2.0,-86.4479554902523,-0.8032642331288344,-2.848679447852761,-0.010045337423312817
+0.9934256055363321,2002.0,14.0,3253.0,2.5,-86.46363424598624,-0.80811,-2.84627,-0.00657
+0.9934606683924532,2016.0,14.0,3247.0,3.0,-86.47931300172019,-0.8068449689440994,-2.8587570807453417,-0.006592670807453417
+0.9935231698500432,1994.0,16.0,3240.0,3.0,-86.49499175745413,-0.8055799378881987,-2.8712441614906834,-0.006615341614906832
+0.9935856713076331,1983.0,18.0,3274.0,2.0,-86.51067051318807,-0.8043149068322981,-2.883731242236025,-0.006638012422360249
+0.9936481727652231,1969.0,16.0,3257.0,2.0,-86.52634926892202,-0.8030498757763975,-2.8962183229813667,-0.006660683229813665
+0.993710674222813,1973.0,22.0,3226.0,2.0,-86.54202802465596,-0.8017848447204969,-2.908705403726708,-0.006683354037267081
+0.993773175680403,1986.0,17.0,3254.0,4.0,-86.5577067803899,-0.8005198136645962,-2.9211924844720496,-0.006706024844720497
+0.9938356771379929,1987.0,16.0,3231.0,2.0,-86.57338553612385,-0.7992547826086956,-2.9336795652173913,-0.006728695652173914
+0.9938981785955829,1954.0,20.0,3226.0,3.0,-86.5890642918578,-0.7979897515527951,-2.946166645962733,-0.006751366459627329
+0.9939606800531728,1976.0,19.0,3227.0,3.0,-86.60474304759174,-0.7967247204968944,-2.9586537267080746,-0.006774037267080746
+0.9940231815107629,1951.0,18.0,3205.0,2.0,-86.62042180332568,-0.7954596894409938,-2.9711408074534162,-0.006796708074534162
+0.9940856829683528,1977.0,18.0,3240.0,2.0,-86.63610055905963,-0.7941946583850932,-2.983627888198758,-0.006819378881987578
+0.9941481844259428,1962.0,18.0,3240.0,3.0,-86.65177931479357,-0.7929296273291926,-2.9961149689440996,-0.006842049689440994
+0.9942106858835328,1972.0,14.0,3263.0,2.0,-86.66745807052752,-0.7916645962732919,-3.008602049689441,-0.0068647204968944105
+0.9942731873411227,2015.0,13.0,3263.0,2.0,-86.68313682626147,-0.7903995652173913,-3.0210891304347824,-0.006887391304347826
+0.9943356887987127,1985.0,16.0,3247.0,2.0,-86.69881558199542,-0.7891345341614907,-3.033576211180124,-0.0069100621118012425
+0.9943981902563026,1982.0,17.0,3255.0,2.0,-86.71449433772936,-0.78786950310559,-3.0460632919254658,-0.006932732919254658
+0.9944606917138926,2013.0,19.0,3240.0,3.0,-86.7301730934633,-0.7866044720496894,-3.0585503726708074,-0.0069554037267080746
+0.9945231931714825,1995.0,18.0,3232.0,2.0,-86.74585184919725,-0.7853394409937888,-3.071037453416149,-0.006978074534161491
+0.9945856946290725,2044.0,18.0,3240.0,2.0,-86.7615306049312,-0.7840744099378882,-3.0835245341614907,-0.0070007453416149066
+0.9946481960866624,1984.0,16.0,3233.0,3.0,-86.77720936066514,-0.7828093788819875,-3.0960116149068324,-0.007023416149068323
+0.9947106975442525,1999.0,16.0,3226.0,2.0,-86.79288811639908,-0.781544347826087,-3.108498695652174,-0.0070460869565217394
+0.9947731990018424,1963.0,21.0,3227.0,2.0,-86.80856687213303,-0.7802793167701864,-3.1209857763975153,-0.007068757763975155
+0.9948357004594324,1993.0,18.0,3238.0,2.0,-86.82424562786697,-0.7790142857142857,-3.133472857142857,-0.0070914285714285714
+0.9948982019170223,1973.0,18.0,3214.0,3.0,-86.83992438360092,-0.7777492546583851,-3.1459599378881986,-0.007114099378881988
+0.9949607033746123,1994.0,18.0,3234.0,5.0,-86.85560313933486,-0.7764842236024845,-3.1584470186335403,-0.0071367701863354034
+0.9950232048322023,2004.0,17.0,3259.0,2.0,-86.8712818950688,-0.7752191925465839,-3.170934099378882,-0.00715944099378882
+0.9950857062897922,2000.0,17.0,3236.0,2.0,-86.88696065080275,-0.7739541614906832,-3.1834211801242236,-0.007182111801242236
+0.9951482077473822,1995.0,16.0,3241.0,2.0,-86.9026394065367,-0.7726891304347826,-3.1959082608695653,-0.007204782608695652
+0.9952107092049721,2011.0,16.0,3262.0,3.0,-86.91831816227064,-0.771424099378882,-3.208395341614907,-0.007227453416149068
+0.9952732106625621,1986.0,21.0,3267.0,2.0,-86.93399691800458,-0.7701590683229813,-3.2208824223602486,-0.007250124223602485
+0.995335712120152,2001.0,19.0,3269.0,2.0,-86.94967567373853,-0.7688940372670807,-3.23336950310559,-0.0072727950310559
+0.995398213577742,1973.0,18.0,3268.0,2.0,-86.96535442947248,-0.7676290062111801,-3.2458565838509315,-0.007295465838509317
+0.995460715035332,1986.0,18.0,3277.0,5.0,-86.98103318520643,-0.7663639751552795,-3.258343664596273,-0.007318136645962732
+0.995523216492922,1989.0,18.0,3249.0,2.0,-86.99671194094037,-0.7650989440993788,-3.2708307453416148,-0.007340807453416149
+0.9955857179505119,1968.0,26.0,3254.0,3.0,-87.01239069667432,-0.7638339130434783,-3.2833178260869564,-0.007363478260869565
+0.9956482194081019,1986.0,20.0,3254.0,2.0,-87.02806945240826,-0.7625688819875777,-3.295804906832298,-0.007386149068322981
+0.9957107208656918,1982.0,13.0,3238.0,3.0,-87.0437482081422,-0.761303850931677,-3.3082919875776398,-0.007408819875776397
+0.9957732223232818,1976.0,16.0,3257.0,2.0,-87.05942696387615,-0.7600388198757764,-3.3207790683229814,-0.007431490683229814
+0.9958357237808717,1993.0,19.0,3248.0,2.0,-87.0751057196101,-0.7587737888198758,-3.333266149068323,-0.007454161490683229
+0.9958982252384617,1958.0,28.0,3246.0,1.0,-87.09078447534404,-0.7575087577639752,-3.3457532298136643,-0.007476832298136646
+0.9959607266960517,1992.0,22.0,3265.0,4.0,-87.10646323107798,-0.7562437267080745,-3.358240310559006,-0.007499503105590062
+0.9960232281536416,1981.0,18.0,3239.0,2.0,-87.12214198681193,-0.7549786956521739,-3.3707273913043476,-0.007522173913043478
+0.9960857296112317,2011.0,17.0,3267.0,3.0,-87.13782074254587,-0.7537136645962733,-3.3832144720496893,-0.007544844720496894
+0.9961482310688216,2019.0,22.0,3274.0,2.0,-87.15349949827981,-0.7524486335403726,-3.395701552795031,-0.0075675155279503106
+0.9962107325264116,2022.0,17.0,3276.0,2.0,-87.16917825401376,-0.751183602484472,-3.4081886335403726,-0.007590186335403726
+0.9962732339840015,2060.0,16.0,3281.0,2.0,-87.1848570097477,-0.7499185714285714,-3.4206757142857143,-0.0076128571428571426
+0.9963357354415915,2028.0,18.0,3278.0,2.0,-87.20053576548165,-0.7486535403726708,-3.433162795031056,-0.007635527950310559
+0.9963982368991814,2015.0,16.0,3287.0,2.0,-87.21621452121559,-0.7473885093167701,-3.4456498757763976,-0.007658198757763975
+0.9964607383567714,2021.0,16.0,3275.0,3.0,-87.23189327694953,-0.7461234782608696,-3.458136956521739,-0.007680869565217391
+0.9965232398143613,2024.0,17.0,3263.0,2.0,-87.24757203268348,-0.744858447204969,-3.4706240372670805,-0.0077035403726708074
+0.9965857412719513,1980.0,20.0,3258.0,2.0,-87.26325078841744,-0.7435934161490683,-3.483111118012422,-0.007726211180124223
+0.9966482427295412,2006.0,19.0,3272.0,2.0,-87.27892954415138,-0.7423283850931677,-3.495598198757764,-0.0077488819875776395
+0.9967107441871312,2039.0,13.0,3250.0,2.0,-87.29460829988533,-0.7410633540372671,-3.5080852795031054,-0.007771552795031056
+0.9967732456447213,1995.0,16.0,3259.0,2.0,-87.31028705561927,-0.7397983229813665,-3.520572360248447,-0.0077942236024844715
+0.9968357471023112,2015.0,17.0,3253.0,3.0,-87.32596581135321,-0.7385332919254658,-3.5330594409937888,-0.007816894409937887
+0.9968982485599012,1992.0,19.0,3245.0,2.0,-87.34164456708716,-0.7372682608695652,-3.5455465217391304,-0.007839565217391304
+0.9969607500174911,2013.0,16.0,3258.0,8.0,-87.3573233228211,-0.7360032298136646,-3.558033602484472,-0.00786223602484472
+0.9970232514750811,2011.0,18.0,3238.0,3.0,-87.37300207855505,-0.7347381987577639,-3.5705206832298133,-0.007884906832298135
+0.997085752932671,2026.0,18.0,3262.0,2.0,-87.38868083428899,-0.7334731677018633,-3.583007763975155,-0.007907577639751553
+0.997148254390261,2043.0,17.0,3272.0,2.0,-87.40435959002293,-0.7322081366459627,-3.5954948447204966,-0.007930248447204968
+0.9972107558478509,2040.0,16.0,3279.0,2.0,-87.42003834575688,-0.7309431055900621,-3.6079819254658383,-0.007952919254658384
+0.9972732573054409,2068.0,18.0,3301.0,3.0,-87.43571710149082,-0.7296780745341614,-3.62046900621118,-0.007975590062111801
+0.9973357587630308,2050.0,17.0,3287.0,2.0,-87.45139585722477,-0.7284130434782609,-3.6329560869565216,-0.007998260869565217
+0.9973982602206208,2034.0,16.0,3289.0,2.0,-87.46707461295871,-0.7271480124223603,-3.6454431677018633,-0.008020931677018632
+0.9974607616782107,2053.0,17.0,3282.0,5.0,-87.48275336869266,-0.7258829813664596,-3.657930248447205,-0.00804360248447205
+0.9975232631358008,2038.0,17.0,3268.0,2.0,-87.4984321244266,-0.724617950310559,-3.6704173291925466,-0.008066273291925465
+0.9975857645933907,2040.0,21.0,3268.0,4.0,-87.51411088016054,-0.7233529192546584,-3.682904409937888,-0.00808894409937888
+0.9976482660509807,2013.0,17.0,3240.0,2.0,-87.5297896358945,-0.7220878881987578,-3.6953914906832295,-0.008111614906832298
+0.9977107675085707,2006.0,18.0,3211.0,2.0,-87.54546839162845,-0.7208228571428571,-3.707878571428571,-0.008134285714285714
+0.9977732689661606,2006.0,16.0,3228.0,2.0,-87.56114714736239,-0.7195578260869565,-3.720365652173913,-0.00815695652173913
+0.9978357704237506,2020.0,17.0,3221.0,2.0,-87.57682590309633,-0.7182927950310559,-3.7328527329192545,-0.008179627329192547
+0.9978982718813405,2013.0,21.0,3225.0,2.0,-87.59250465883028,-0.7170277639751552,-3.745339813664596,-0.008202298136645962
+0.9979607733389305,2037.0,17.0,3245.0,4.0,-87.60818341456422,-0.7157627329192546,-3.757826894409938,-0.008224968944099378
+0.9980232747965204,2006.0,20.0,3254.0,2.0,-87.62386217029817,-0.714497701863354,-3.770313975155279,-0.008247639751552795
+0.9980857762541104,2029.0,18.0,3249.0,4.0,-87.63954092603211,-0.7132326708074535,-3.782801055900621,-0.00827031055900621
+0.9981482777117003,2079.0,16.0,3295.0,2.0,-87.65521968176606,-0.7119676397515527,-3.7952881366459623,-0.008292981366459626
+0.9982107791692904,2060.0,16.0,3246.0,2.0,-87.6708984375,-0.7107026086956522,-3.807775217391304,-0.008315652173913043
+0.9982732806268803,2038.0,16.0,3239.0,2.0,-87.68657719323394,-0.7094375776397516,-3.8202622981366456,-0.008338322981366459
+0.9983357820844703,2064.0,17.0,3252.0,2.0,-87.70225594896789,-0.7081725465838509,-3.8327493788819873,-0.008360993788819875
+0.9983982835420602,2009.0,16.0,3233.0,2.0,-87.71793470470183,-0.7069075155279503,-3.845236459627329,-0.008383664596273292
+0.9984607849996502,2020.0,16.0,3233.0,2.0,-87.73361346043578,-0.7056424844720497,-3.8577235403726706,-0.008406335403726707
+0.9985232864572402,2025.0,16.0,3224.0,2.0,-87.74929221616972,-0.7043774534161491,-3.8702106211180123,-0.008429006211180123
+0.9985857879148301,2021.0,15.0,3225.0,2.0,-87.76497097190367,-0.7031124223602484,-3.8826977018633535,-0.00845167701863354
+0.9986482893724201,2064.0,17.0,3204.0,2.0,-87.78064972763761,-0.7018473913043478,-3.8951847826086956,-0.008474347826086956
+0.99871079083001,2029.0,21.0,3203.0,5.0,-87.79632848337155,-0.7005823602484472,-3.907671863354037,-0.008497018633540371
+0.9987732922876,2023.0,17.0,3214.0,2.0,-87.8120072391055,-0.6993173291925465,-3.920158944099379,-0.008519689440993787
+0.9988357937451899,2048.0,17.0,3202.0,4.0,-87.82768599483946,-0.6980522981366459,-3.93264602484472,-0.008542360248447204
+0.99889829520278,2026.0,18.0,3201.0,2.0,-87.8433647505734,-0.6967872670807453,-3.945133105590062,-0.00856503105590062
+0.9989607966603699,2003.0,20.0,3212.0,2.0,-87.85904350630734,-0.6955222360248448,-3.9576201863354035,-0.008587701863354037
+0.9990232981179599,2005.0,18.0,3208.0,2.0,-87.87472226204129,-0.694257204968944,-3.970107267080745,-0.008610372670807453
+0.9990857995755498,2014.0,18.0,3204.0,2.0,-87.89040101777523,-0.6929921739130435,-3.982594347826087,-0.008633043478260868
+0.9991483010331398,2034.0,17.0,3214.0,2.0,-87.90607977350918,-0.6917271428571429,-3.995081428571428,-0.008655714285714284
+0.9992108024907297,2017.0,19.0,3197.0,4.0,-87.92175852924312,-0.6904621118012422,-4.00756850931677,-0.008678385093167701
+0.9992733039483197,1992.0,18.0,3181.0,2.0,-87.93743728497707,-0.6891970807453416,-4.020055590062111,-0.008701055900621117
+0.9993358054059096,2014.0,16.0,3198.0,3.0,-87.95311604071101,-0.687932049689441,-4.032542670807453,-0.008723726708074534
+0.9993983068634996,2063.0,13.0,3208.0,2.0,-87.96879479644495,-0.6866670186335404,-4.045029751552795,-0.00874639751552795
+0.9994608083210896,2025.0,17.0,3202.0,2.0,-87.9844735521789,-0.6854019875776397,-4.057516832298136,-0.008769068322981365
+0.9995233097786795,2011.0,11.0,3213.0,2.0,-88.00015230791284,-0.6841369565217391,-4.070003913043478,-0.00879173913043478
+0.9995858112362696,2042.0,16.0,3193.0,2.0,-88.01583106364679,-0.6828719254658385,-4.08249099378882,-0.008814409937888198
+0.9996483126938595,2021.0,18.0,3196.0,2.0,-88.03150981938073,-0.6816068944099378,-4.094978074534161,-0.008837080745341614
+0.9997108141514495,2056.0,20.0,3209.0,4.0,-88.04718857511467,-0.6803418633540372,-4.1074651552795025,-0.008859751552795031
+0.9997733156090394,2001.0,17.0,3183.0,2.0,-88.06286733084862,-0.6790768322981366,-4.119952236024845,-0.008882422360248447
+0.9998358170666294,1998.0,13.0,3206.0,2.0,-88.07854608658256,-0.6778118012422361,-4.132439316770186,-0.008905093167701862
+0.9998983185242193,2017.0,17.0,3192.0,2.0,-88.0942248423165,-0.6765467701863354,-4.144926397515528,-0.008927763975155278
+0.9999608199818093,1995.0,16.0,3195.0,2.0,-88.10990359805047,-0.6752817391304348,-4.157413478260869,-0.008950434782608695
+1.0000233214393992,2035.0,16.0,3212.0,3.0,-88.12558235378441,-0.6740167080745342,-4.16990055900621,-0.00897310559006211
+1.000085822896989,1979.0,16.0,3199.0,2.0,-88.14126110951835,-0.6727516770186335,-4.1823876397515525,-0.008995776397515528
+1.0001483243545792,1987.0,20.0,3200.0,2.0,-88.1569398652523,-0.6714866459627329,-4.194874720496895,-0.009018447204968943
+1.0002108258121691,1962.0,17.0,3168.0,3.0,-88.17261862098624,-0.6702216149068323,-4.207361801242236,-0.009041118012422359
+1.000273327269759,1921.0,24.0,3165.0,2.0,-88.18829737672019,-0.6689565838509317,-4.219848881987577,-0.009063788819875775
+1.0003358287273492,1962.0,18.0,3166.0,4.0,-88.20397613245413,-0.667691552795031,-4.232335962732919,-0.009086459627329192
+1.000398330184939,1999.0,18.0,3176.0,2.0,-88.21965488818807,-0.6664265217391304,-4.24482304347826,-0.009109130434782607
+1.000460831642529,1970.0,17.0,3174.0,3.0,-88.23533364392202,-0.6651614906832298,-4.257310124223602,-0.009131801242236023
+1.0005233331001189,1955.0,17.0,3196.0,2.0,-88.25101239965596,-0.6638964596273291,-4.269797204968944,-0.00915447204968944
+1.000585834557709,1987.0,14.0,3193.0,2.0,-88.2666911553899,-0.6626314285714285,-4.282284285714285,-0.009177142857142856
+1.000648336015299,1961.0,17.0,3179.0,2.0,-88.28236991112385,-0.661366397515528,-4.294771366459627,-0.009199813664596272
+1.0007108374728888,1917.0,27.0,3174.0,5.0,-88.2980486668578,-0.6601013664596274,-4.307258447204968,-0.009222484472049689
+1.0007733389304787,1964.0,14.0,3196.0,2.0,-88.31372742259174,-0.6588363354037267,-4.31974552795031,-0.009245155279503104
+1.0008358403880688,1959.0,18.0,3210.0,4.0,-88.32940617832568,-0.6575713043478261,-4.3322326086956515,-0.00926782608695652
+1.0008983418456587,1987.0,17.0,3179.0,1.0,-88.34508493405963,-0.6563062732919255,-4.344719689440994,-0.009290496894409937
+1.0009608433032486,1969.0,18.0,3162.0,3.0,-88.36076368979357,-0.6550412422360248,-4.357206770186335,-0.009313167701863353
+1.0010233447608385,2005.0,18.0,3163.0,2.0,-88.37644244552752,-0.6537762111801242,-4.369693850931677,-0.009335838509316768
+1.0010858462184287,1964.0,19.0,3145.0,2.0,-88.39212120126146,-0.6525111801242236,-4.382180931677018,-0.009358509316770184
+1.0011483476760186,1971.0,18.0,3157.0,2.0,-88.40779995699542,-0.651246149068323,-4.394668012422359,-0.009381180124223601
+1.0012108491336085,1962.0,22.0,3133.0,6.0,-88.42347871272936,-0.6499811180124223,-4.4071550931677015,-0.009403850931677017
+1.0012733505911986,1932.0,30.0,3127.0,2.0,-88.4391574684633,-0.6487160869565217,-4.419642173913043,-0.009426521739130434
+1.0013358520487885,1954.0,21.0,3138.0,4.0,-88.45483622419725,-0.6474510559006211,-4.432129254658385,-0.00944919254658385
+1.0013983535063784,1952.0,17.0,3098.0,2.0,-88.4705149799312,-0.6461860248447204,-4.444616335403726,-0.009471863354037265
+1.0014608549639683,1954.0,17.0,3106.0,2.0,-88.48619373566514,-0.6449209937888198,-4.457103416149068,-0.00949453416149068
+1.0015233564215584,1963.0,20.0,3121.0,3.0,-88.50187249139908,-0.6436559627329193,-4.469590496894409,-0.009517204968944098
+1.0015858578791483,1964.0,20.0,3118.0,2.0,-88.51755124713303,-0.6423909316770187,-4.4820775776397515,-0.009539875776397514
+1.0016483593367382,1983.0,18.0,3143.0,1.0,-88.53323000286697,-0.641125900621118,-4.494564658385093,-0.009562546583850931
+1.0017108607943281,1933.0,28.0,3133.0,5.0,-88.54890875860092,-0.6398608695652174,-4.507051739130434,-0.009585217391304347
+1.0017733622519183,1989.0,16.0,3146.0,2.0,-88.56458751433486,-0.6385958385093168,-4.519538819875776,-0.009607888198757762
+1.0018358637095082,1980.0,19.0,3174.0,4.0,-88.5802662700688,-0.6373308074534161,-4.532025900621117,-0.009630559006211178
+1.001898365167098,2006.0,15.0,3160.0,3.0,-88.59594502580275,-0.6360657763975155,-4.544512981366459,-0.009653229813664595
+1.001960866624688,1988.0,16.0,3146.0,2.0,-88.6116237815367,-0.6348007453416149,-4.5570000621118005,-0.00967590062111801
+1.002023368082278,2015.0,19.0,3158.0,2.0,-88.62730253727064,-0.6335357142857143,-4.569487142857143,-0.009698571428571428
+1.002085869539868,1980.0,18.0,3147.0,2.0,-88.64298129300458,-0.6322706832298136,-4.581974223602484,-0.009721242236024843
+1.002148370997458,1974.0,20.0,3158.0,2.0,-88.65866004873853,-0.631005652173913,-4.594461304347826,-0.009743913043478259
+1.002210872455048,1971.0,17.0,3127.0,2.0,-88.67433880447248,-0.6297406211180124,-4.606948385093167,-0.009766583850931675
+1.002273373912638,1966.0,22.0,3126.0,2.0,-88.69001756020643,-0.6284755900621117,-4.619435465838508,-0.009789254658385092
+1.0023358753702278,1971.0,16.0,3131.0,2.0,-88.70569631594037,-0.6272105590062111,-4.6319225465838505,-0.009811925465838508
+1.0023983768278177,2006.0,16.0,3128.0,2.0,-88.72137507167432,-0.6259455279503106,-4.644409627329192,-0.009834596273291925
+1.0024608782854079,1979.0,19.0,3141.0,2.0,-88.73705382740826,-0.62468049689441,-4.656896708074534,-0.00985726708074534
+1.0025233797429978,1982.0,20.0,3128.0,2.0,-88.7527325831422,-0.6234154658385093,-4.669383788819875,-0.009879937888198756
+1.0025858812005877,2002.0,16.0,3130.0,2.0,-88.76841133887615,-0.6221504347826087,-4.681870869565217,-0.009902608695652172
+1.0026483826581776,1992.0,17.0,3142.0,3.0,-88.7840900946101,-0.6208854037267081,-4.694357950310558,-0.009925279503105589
+1.0027108841157677,2037.0,12.0,3151.0,2.0,-88.79976885034404,-0.6196203726708074,-4.7068450310559005,-0.009947950310559004
+1.0027733855733576,2004.0,18.0,3143.0,2.0,-88.81544760607798,-0.6183553416149068,-4.719332111801242,-0.009970621118012422
+1.0028358870309475,1996.0,14.0,3164.0,4.0,-88.83112636181193,-0.6170903105590062,-4.731819192546583,-0.009993291925465837
+1.0028983884885374,2023.0,15.0,3143.0,2.0,-88.84680511754587,-0.6158252795031056,-4.744306273291925,-0.010015962732919253
+1.0029608899461275,2002.0,18.0,3130.0,3.0,-88.86248387327981,-0.6145602484472049,-4.756793354037266,-0.010038633540372668
+1.0030233914037174,1962.0,18.0,3130.0,2.0,-88.87816262901376,-0.6132952173913043,-4.769280434782608,-0.010061304347826086
+1.0030858928613073,1994.0,16.0,3118.0,2.0,-88.8938413847477,-0.6120301863354037,-4.7817675155279495,-0.010083975155279501
+1.0031483943188975,1983.0,20.0,3104.0,2.0,-88.90952014048165,-0.610765155279503,-4.794254596273292,-0.010106645962732919
+1.0032108957764874,1991.0,21.0,3105.0,2.0,-88.92519889621559,-0.6095001242236024,-4.806741677018633,-0.010129316770186334
+1.0032733972340773,2001.0,16.0,3105.0,2.0,-88.94087765194953,-0.6082350931677019,-4.819228757763975,-0.01015198757763975
+1.0033358986916672,1995.0,19.0,3116.0,8.0,-88.95655640768348,-0.6069700621118013,-4.831715838509316,-0.010174658385093165
+1.0033984001492573,2038.0,18.0,3111.0,2.0,-88.97223516341744,-0.6057050310559007,-4.844202919254657,-0.010197329192546583
+1.0034602076124566,2021.0,18.0,3114.5,2.0,-88.98791391915138,-0.60444,-4.8566899999999995,-0.010219999999999998
+1.0034609016068472,2004.0,18.0,3118.0,2.0,-89.00359267488533,-0.6087080368098159,-4.848763006134969,-0.0072462576687116545
+1.003523403064437,1997.0,20.0,3130.0,2.0,-89.01927143061927,-0.6129760736196319,-4.840836012269938,-0.004272515337423312
+1.003585904522027,2023.0,14.0,3106.0,2.0,-89.03495018635321,-0.6172441104294478,-4.832909018404908,-0.0012987730061349689
+1.0036484059796171,2004.0,17.0,3091.0,2.0,-89.05062894208716,-0.6215121472392637,-4.824982024539877,0.0016749693251533748
+1.003710907437207,2051.0,16.0,3097.0,2.0,-89.0663076978211,-0.6257801840490798,-4.8170550306748465,0.0046487116564417185
+1.003773408894797,2019.0,20.0,3094.0,3.0,-89.08198645355505,-0.6300482208588957,-4.809128036809815,0.0076224539877300605
+1.003835910352387,2011.0,17.0,3108.0,5.0,-89.09766520928899,-0.6343162576687116,-4.8012010429447844,0.010596196319018406
+1.003898411809977,2036.0,14.0,3101.0,2.0,-89.11334396502293,-0.6385842944785276,-4.793274049079754,0.013569938650306748
+1.0039609132675669,2016.0,18.0,3098.0,3.0,-89.12902272075688,-0.6428523312883435,-4.785347055214723,0.016543680981595088
+1.0040234147251568,2039.0,26.0,3114.0,2.0,-89.14470147649082,-0.6471203680981594,-4.777420061349693,0.019517423312883433
+1.004085916182747,2002.0,18.0,3083.0,3.0,-89.16038023222477,-0.6513884049079754,-4.769493067484662,0.02249116564417178
+1.0041484176403368,1986.0,28.0,3065.0,3.0,-89.17605898795871,-0.6556564417177914,-4.7615660736196315,0.025464907975460117
+1.0042109190979267,1995.0,16.0,3070.0,1.0,-89.19173774369266,-0.6599244785276073,-4.753639079754601,0.028438650306748463
+1.0042734205555166,2017.0,20.0,3071.0,2.0,-89.2074164994266,-0.6641925153374233,-4.74571208588957,0.03141239263803681
+1.0043359220131067,1997.0,19.0,3074.0,2.0,-89.22309525516054,-0.6684605521472392,-4.73778509202454,0.03438613496932515
+1.0043984234706966,1950.0,18.0,3081.0,2.0,-89.23877401089449,-0.6727285889570551,-4.729858098159509,0.03735987730061349
+1.0044609249282865,1979.0,18.0,3090.0,2.0,-89.25445276662845,-0.6769966257668711,-4.721931104294478,0.04033361963190184
+1.0045234263858764,1960.0,20.0,3065.0,2.0,-89.27013152236239,-0.681264662576687,-4.714004110429447,0.043307361963190176
+1.0045859278434666,1967.0,16.0,3069.0,1.0,-89.28581027809633,-0.685532699386503,-4.706077116564416,0.04628110429447852
+1.0046484293010565,1986.0,21.0,3069.0,4.0,-89.30148903383028,-0.689800736196319,-4.698150122699386,0.04925484662576687
+1.0047109307586464,2004.0,20.0,3106.0,2.0,-89.31716778956422,-0.6940687730061349,-4.690223128834355,0.052228588957055205
+1.0047734322162365,2004.0,18.0,3128.0,0.0,-89.33284654529817,-0.6983368098159508,-4.682296134969325,0.05520233128834356
+1.0048359336738264,1987.0,16.0,3111.0,2.0,-89.34852530103211,-0.7026048466257668,-4.674369141104294,0.05817607361963189
+1.0048984351314163,1993.0,16.0,3118.0,2.0,-89.36420405676606,-0.7068728834355827,-4.666442147239263,0.061149815950920235
+1.0049019607843137,1998.5,18.5,3127.0,3.5,-89.3798828125,-0.7111409202453988,-4.658515153374233,0.06412355828220859
+1.0049609365890062,2004.0,21.0,3136.0,5.0,-89.39548068576389,-0.7154089570552147,-4.650588159509202,0.06709730061349693
+1.0050234380465963,1972.0,22.0,3163.0,2.0,-89.41107855902777,-0.7196769938650306,-4.642661165644172,0.07007104294478528
+1.0050859395041862,2006.0,20.0,3154.0,2.0,-89.42667643229167,-0.7239450306748466,-4.63473417177914,0.07304478527607362
+1.0051484409617761,1995.0,24.0,3142.0,3.0,-89.44227430555556,-0.7282130674846625,-4.62680717791411,0.07601852760736195
+1.005210942419366,2014.0,12.0,3169.0,2.0,-89.45787217881944,-0.7324811042944784,-4.618880184049079,0.0789922699386503
+1.0052734438769562,2042.0,14.0,3134.0,2.0,-89.47347005208333,-0.7367491411042945,-4.610953190184048,0.08196601226993865
+1.005335945334546,2026.0,17.0,3118.0,2.0,-89.48906792534723,-0.7410171779141104,-4.603026196319018,0.08493975460122699
+1.005398446792136,2065.0,19.0,3116.0,4.0,-89.50466579861111,-0.7452852147239263,-4.595099202453987,0.08791349693251534
+1.0054609482497259,2043.0,25.0,3122.0,4.0,-89.520263671875,-0.7495532515337423,-4.587172208588957,0.09088723926380368
+1.005523449707316,2025.0,16.0,3139.0,3.0,-89.53586154513889,-0.7538212883435582,-4.579245214723926,0.09386098159509203
+1.005585951164906,2054.0,14.0,3102.0,2.0,-89.55145941840277,-0.7580893251533742,-4.571318220858895,0.09683472392638036
+1.0056484526224958,2024.0,18.0,3096.0,2.0,-89.56705729166667,-0.7623573619631901,-4.563391226993865,0.0998084662576687
+1.005710954080086,2005.0,17.0,3096.0,2.0,-89.58265516493056,-0.7666253987730061,-4.555464233128834,0.10278220858895705
+1.0057734555376758,2015.0,18.0,3122.0,2.0,-89.59825303819444,-0.7708934355828221,-4.547537239263804,0.1057559509202454
+1.0058359569952657,1982.0,16.0,3098.0,2.0,-89.61385091145833,-0.775161472392638,-4.539610245398772,0.10872969325153374
+1.0058984584528556,1991.0,16.0,3105.0,2.0,-89.62944878472223,-0.7794295092024539,-4.5316832515337415,0.11170343558282209
+1.0059609599104458,2005.0,21.0,3096.0,7.0,-89.64504665798611,-0.7836975460122699,-4.523756257668711,0.11467717791411042
+1.0060234613680357,1977.0,21.0,3071.0,2.0,-89.66064453125,-0.7879655828220858,-4.51582926380368,0.11765092024539876
+1.0060859628256256,2004.0,24.0,3067.0,2.0,-89.67624240451389,-0.7922336196319018,-4.50790226993865,0.12062466257668712
+1.0061484642832155,1997.0,23.0,3069.0,2.0,-89.69184027777777,-0.7965016564417178,-4.499975276073619,0.12359840490797545
+1.0062109657408056,2007.0,17.0,3096.0,2.0,-89.70743815104167,-0.8007696932515337,-4.4920482822085885,0.12657214723926377
+1.0062734671983955,2034.0,14.0,3067.0,3.0,-89.72303602430556,-0.8050377300613496,-4.484121288343558,0.12954588957055213
+1.0063359686559854,2015.0,19.0,3065.0,3.0,-89.73863389756944,-0.8093057668711656,-4.476194294478527,0.13251963190184046
+1.0063984701135753,2041.0,18.0,3066.0,2.0,-89.75423177083333,-0.8135738036809815,-4.468267300613497,0.13549337423312882
+1.0064609715711654,2018.0,19.0,3048.0,3.0,-89.76982964409723,-0.8178418404907974,-4.460340306748465,0.13846711656441715
+1.0065234730287553,2003.0,16.0,3055.0,2.0,-89.78542751736111,-0.8221098773006135,-4.452413312883435,0.1414408588957055
+1.0065859744863452,2017.0,16.0,3035.0,2.0,-89.801025390625,-0.8263779141104294,-4.444486319018404,0.14441460122699384
+1.0066484759439354,2009.0,20.0,3048.0,2.0,-89.81662326388889,-0.8306459509202453,-4.4365593251533735,0.14738834355828218
+1.0067109774015253,2008.0,20.0,3053.0,2.0,-89.83222113715277,-0.8349139877300613,-4.428632331288343,0.15036208588957053
+1.0067734788591152,2004.0,17.0,3055.0,2.0,-89.84781901041667,-0.8391820245398772,-4.420705337423312,0.15333582822085887
+1.006835980316705,1987.0,19.0,3051.0,4.0,-89.86341688368056,-0.8434500613496931,-4.412778343558282,0.15630957055214723
+1.0068984817742952,1995.0,19.0,3029.0,2.0,-89.87901475694444,-0.8477180981595092,-4.404851349693251,0.15928331288343556
+1.006960983231885,1998.0,19.0,3002.0,3.0,-89.89461263020833,-0.8519861349693251,-4.3969243558282205,0.1622570552147239
+1.007023484689475,2019.0,21.0,3006.0,2.0,-89.91021050347223,-0.856254171779141,-4.38899736196319,0.16523079754601225
+1.007085986147065,1994.0,21.0,3011.0,2.0,-89.92580837673611,-0.860522208588957,-4.381070368098159,0.16820453987730058
+1.007148487604655,1991.0,18.0,3016.0,4.0,-89.94140625,-0.8647902453987729,-4.373143374233129,0.17117828220858894
+1.007210989062245,2002.0,18.0,3047.0,2.0,-89.95700412326389,-0.8690582822085888,-4.365216380368097,0.17415202453987727
+1.0072734905198348,2022.0,17.0,3023.0,2.0,-89.97260199652777,-0.8733263190184049,-4.357289386503067,0.17712576687116563
+1.007335991977425,2008.0,28.0,3029.0,4.0,-89.98819986979167,-0.8775943558282208,-4.349362392638036,0.18009950920245396
+1.0073984934350149,2017.0,18.0,3030.0,2.0,-90.00379774305556,-0.8818623926380367,-4.341435398773005,0.1830732515337423
+1.0074609948926048,2008.0,18.0,3030.0,3.0,-90.01939561631944,-0.8861304294478527,-4.333508404907975,0.18604699386503065
+1.0075234963501947,1995.0,16.0,3035.0,2.0,-90.03499348958333,-0.8903984662576686,-4.325581411042944,0.18902073619631898
+1.0075859978077848,2004.0,20.0,3022.0,3.0,-90.05059136284723,-0.8946665030674845,-4.317654417177914,0.19199447852760734
+1.0076484992653747,2002.0,21.0,3024.0,2.0,-90.06618923611111,-0.8989345398773005,-4.309727423312883,0.19496822085889567
+1.0077110007229646,1980.0,19.0,3043.0,2.0,-90.081787109375,-0.9032025766871165,-4.3018004294478525,0.19794196319018403
+1.0077735021805545,1996.0,18.0,3021.0,2.0,-90.09738498263889,-0.9074706134969324,-4.293873435582822,0.20091570552147237
+1.0078360036381446,1971.0,21.0,3023.0,4.0,-90.11298285590277,-0.9117386503067484,-4.28594644171779,0.2038894478527607
+1.0078985050957345,1983.0,22.0,3037.0,2.0,-90.12858072916667,-0.9160066871165643,-4.27801944785276,0.20686319018404906
+1.0079610065533244,1994.0,21.0,3030.0,3.0,-90.14417860243056,-0.9202747239263802,-4.270092453987729,0.2098369325153374
+1.0080235080109143,1954.0,18.0,3042.0,3.0,-90.15977647569444,-0.9245427607361962,-4.262165460122699,0.21281067484662575
+1.0080860094685045,1993.0,24.0,3061.0,2.0,-90.17537434895833,-0.9288107975460121,-4.254238466257668,0.21578441717791408
+1.0081485109260944,1997.0,26.0,3085.0,2.0,-90.19097222222223,-0.9330788343558281,-4.246311472392637,0.2187581595092024
+1.0082110123836843,1995.0,17.0,3117.0,2.0,-90.20657009548611,-0.9373468711656441,-4.238384478527607,0.22173190184049077
+1.0082735138412744,2001.0,16.0,3117.0,2.0,-90.22216796875,-0.94161490797546,-4.230457484662576,0.2247056441717791
+1.0083360152988643,1982.0,28.0,3088.0,2.0,-90.23776584201389,-0.9458829447852759,-4.222530490797546,0.22767938650306746
+1.0083985167564542,1956.0,21.0,3081.0,2.0,-90.25336371527777,-0.9501509815950919,-4.214603496932515,0.2306531288343558
+1.008461018214044,1967.0,20.0,3085.0,2.0,-90.26896158854167,-0.9544190184049078,-4.206676503067484,0.23362687116564415
+1.0085235196716342,1964.0,23.0,3055.0,2.0,-90.28455946180556,-0.9586870552147237,-4.198749509202454,0.23660061349693248
+1.0085860211292241,1958.0,25.0,3046.0,2.0,-90.30015733506944,-0.9629550920245398,-4.190822515337423,0.23957435582822081
+1.008648522586814,1961.0,22.0,3036.0,2.0,-90.31575520833333,-0.9672231288343557,-4.182895521472392,0.24254809815950917
+1.008711024044404,1995.0,21.0,3055.0,4.0,-90.33135308159723,-0.9714911656441716,-4.174968527607361,0.2455218404907975
+1.008773525501994,1948.0,18.0,3037.0,1.0,-90.34695095486111,-0.9757592024539876,-4.1670415337423306,0.24849558282208584
+1.008836026959584,1934.0,22.0,3030.0,3.0,-90.362548828125,-0.9800272392638035,-4.1591145398773,0.2514693251533742
+1.0088985284171739,1931.0,22.0,3042.0,2.0,-90.37814670138889,-0.9842952760736194,-4.151187546012269,0.25444306748466256
+1.0089610298747638,1942.0,23.0,3027.0,2.0,-90.39374457465277,-0.9885633128834355,-4.143260552147239,0.2574168098159509
+1.009023531332354,1932.0,18.0,3049.0,2.0,-90.40934244791667,-0.9928313496932515,-4.135333558282208,0.2603905521472392
+1.0090860327899438,1945.0,19.0,3067.0,2.0,-90.42494032118056,-0.9970993865030673,-4.127406564417178,0.26336429447852755
+1.0091485342475337,1956.0,23.0,3054.0,2.0,-90.44053819444444,-1.0013674233128833,-4.119479570552147,0.26633803680981594
+1.0092110357051238,1930.0,20.0,3079.0,4.0,-90.45613606770833,-1.0056354601226993,-4.1115525766871155,0.26931177914110427
+1.0092735371627137,1940.0,17.0,3067.0,3.0,-90.47173394097223,-1.0099034969325151,-4.103625582822085,0.2722855214723926
+1.0093360386203036,1944.0,24.0,3054.0,3.0,-90.48733181423611,-1.0141715337423312,-4.095698588957054,0.27525926380368093
+1.0093985400778935,1910.0,18.0,3041.0,2.0,-90.5029296875,-1.0184395705521472,-4.087771595092024,0.27823300613496926
+1.0094610415354837,1928.0,17.0,3020.0,2.0,-90.51852756076389,-1.022707607361963,-4.079844601226993,0.28120674846625765
+1.0095235429930736,1898.0,19.0,2997.0,2.0,-90.53412543402777,-1.026975644171779,-4.0719176073619625,0.284180490797546
+1.0095860444506635,1905.0,24.0,3004.0,2.0,-90.54972330729167,-1.031243680981595,-4.063990613496932,0.2871542331288343
+1.0096485459082534,1918.0,21.0,2992.0,2.0,-90.56532118055556,-1.0355117177914108,-4.056063619631901,0.29012797546012264
+1.0097110473658435,1940.0,20.0,2995.0,4.0,-90.58091905381944,-1.0397797546012268,-4.048136625766871,0.29310171779141103
+1.0097735488234334,1907.0,23.0,2998.0,2.0,-90.59651692708333,-1.0440477914110429,-4.04020963190184,0.29607546012269936
+1.0098360502810233,1916.0,23.0,2988.0,3.0,-90.61211480034723,-1.0483158282208587,-4.0322826380368095,0.2990492024539877
+1.0098985517386132,1907.0,23.0,3009.0,3.0,-90.62771267361111,-1.0525838650306747,-4.024355644171779,0.302022944785276
+1.0099610531962033,1918.0,21.0,3006.0,2.0,-90.643310546875,-1.0568519018404907,-4.016428650306748,0.30499668711656436
+1.0100235546537932,1933.0,19.0,3017.0,2.0,-90.65890842013889,-1.0611199386503065,-4.008501656441717,0.30797042944785274
+1.0100860561113831,1934.0,18.0,3019.0,2.0,-90.67450629340277,-1.0653879754601225,-4.000574662576686,0.3109441717791411
+1.0101485575689733,1948.0,18.0,3015.0,2.0,-90.69010416666667,-1.0696560122699386,-3.9926476687116557,0.3139179141104294
+1.0102110590265632,1912.0,18.0,3005.0,3.0,-90.70570203993056,-1.0739240490797544,-3.984720674846625,0.31689165644171774
+1.010273560484153,1929.0,18.0,3001.0,2.0,-90.72129991319444,-1.0781920858895704,-3.9767936809815945,0.31986539877300607
+1.010336061941743,1941.0,26.0,3005.0,2.0,-90.73689778645833,-1.0824601226993864,-3.968866687116564,0.32283914110429446
+1.010398563399333,1909.0,20.0,3019.0,2.0,-90.75249565972223,-1.0867281595092022,-3.9609396932515333,0.3258128834355828
+1.010461064856923,1941.0,18.0,3029.0,2.0,-90.76809353298611,-1.0909961963190182,-3.9530126993865027,0.3287866257668711
+1.010523566314513,1918.0,18.0,3032.0,2.0,-90.78369140625,-1.0952642331288343,-3.9450857055214716,0.33176036809815945
+1.0105860677721028,1933.0,20.0,3051.0,4.0,-90.79928927951389,-1.09953226993865,-3.937158711656441,0.3347341104294478
+1.010648569229693,1949.0,31.0,3040.0,2.0,-90.81488715277777,-1.103800306748466,-3.9292317177914104,0.33770785276073617
+1.0107110706872828,1916.0,20.0,3056.0,3.0,-90.83048502604167,-1.108068343558282,-3.92130472392638,0.3406815950920245
+1.0107735721448727,1939.0,20.0,3078.0,2.0,-90.84608289930556,-1.112336380368098,-3.913377730061349,0.34365533742331283
+1.0108360736024629,1930.0,26.0,3084.0,2.0,-90.86168077256944,-1.116604417177914,-3.905450736196318,0.34662907975460117
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+2.057672986776744,1949.0,18.0,3099.0,2.0,-199.35167100694446,0.038488466257668705,-1.021852208588957,-0.0009270552147239266
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+2.058548007183003,1952.0,14.0,3123.0,2.0,-199.36116536458334,0.0330963190184049,-1.0226673006134968,-0.003246932515337424
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+2.0586730100981834,1946.0,18.0,3097.0,2.0,-199.36252170138889,0.03232601226993865,-1.0227837423312882,-0.003578343558282209
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+2.0590480188437232,1933.0,16.0,3094.0,2.0,-199.36659071180554,0.030015092024539877,-1.0231330674846624,-0.004572576687116565
+2.059110520301313,1990.0,18.0,3098.0,3.0,-199.36726888020834,0.029629938650306747,-1.023191288343558,-0.004738282208588958
+2.059173021758903,1953.0,18.0,3104.0,3.0,-199.36794704861111,0.029244785276073618,-1.0232495092024538,-0.00490398773006135
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+2.0594230275892627,1995.0,17.0,3115.0,3.0,-199.37065972222223,0.027704171779141105,-1.0234823926380368,-0.005566809815950921
+2.059485529046853,1940.0,18.0,3098.0,4.0,-199.371337890625,0.027319018404907976,-1.0235406134969325,-0.005732515337423314
+2.059548030504443,1914.0,18.0,3077.0,2.0,-199.37201605902777,0.026933865030674846,-1.0235988343558282,-0.005898220858895706
+2.059610531962033,1919.0,17.0,3094.0,4.0,-199.37269422743054,0.026548711656441716,-1.0236570552147237,-0.006063926380368099
+2.0596730334196227,1946.0,21.0,3097.0,2.0,-199.37337239583334,0.026163558282208586,-1.0237152760736195,-0.006229631901840491
+2.0597355348772126,1934.0,17.0,3087.0,2.0,-199.37405056423611,0.02577840490797546,-1.0237734969325152,-0.006395337423312884
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+2.0599230392499823,1939.0,20.0,3084.0,2.0,-199.37608506944446,0.024622944785276074,-1.0239481595092024,-0.0068924539877300624
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+2.0600480421651626,1939.0,16.0,3092.0,2.0,-199.37744140625,0.023852638036809815,-1.0240646012269938,-0.0072238650306748475
+2.0601105436227525,1977.0,14.0,3085.0,3.0,-199.37811957465277,0.023467484662576688,-1.0241228220858896,-0.007389570552147241
+2.0601730450803424,1949.0,18.0,3093.0,4.0,-199.37879774305554,0.02308233128834356,-1.024181042944785,-0.007555276073619633
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+2.060298047995522,1969.0,16.0,3096.0,2.0,-199.38015407986111,0.0223120245398773,-1.0242974846625765,-0.007886687116564418
+2.060360549453112,1947.0,17.0,3092.0,2.0,-199.38083224826389,0.021926871165644173,-1.0243557055214723,-0.008052392638036811
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+2.0605480538258822,1922.0,18.0,3096.0,2.0,-199.38286675347223,0.020771411042944787,-1.0245303680981594,-0.00854950920245399
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+2.060673056741062,1946.0,22.0,3098.0,2.0,-199.38422309027777,0.020001104294478527,-1.024646809815951,-0.008880920245398775
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+2.061110566944192,1943.0,22.0,3110.0,3.0,-199.38897026909723,0.017305030674846626,-1.0250543558282208,-0.010040858895705523
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+2.0614230742321418,1965.0,18.0,3116.0,2.0,-199.39236111111111,0.015379263803680984,-1.0253454601226992,-0.010869386503067485
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+2.0616105786049115,1950.0,16.0,3110.0,2.0,-199.39439561631946,0.014223803680981598,-1.0255201226993864,-0.011366503067484664
+2.0616730800625014,1947.0,18.0,3097.0,3.0,-199.39507378472223,0.013838650306748468,-1.0255783435582821,-0.011532208588957057
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+2.0618605844352715,1961.0,25.0,3105.0,4.0,-199.39710828993054,0.012683190184049082,-1.0257530061349691,-0.012029325153374234
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+2.0620480888080412,1951.0,17.0,3099.0,2.0,-199.39914279513889,0.011527730061349696,-1.0259276687116563,-0.012526441717791412
+2.062110590265631,1909.0,24.0,3085.0,4.0,-199.39982096354166,0.011142576687116566,-1.025985889570552,-0.012692147239263806
+2.062173091723221,1957.0,16.0,3096.0,2.0,-199.40049913194446,0.010757423312883437,-1.0260441104294478,-0.012857852760736197
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+2.0622980946384013,1965.0,18.0,3102.0,3.0,-199.40185546875,0.009987116564417177,-1.0261605521472392,-0.013189263803680983
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+2.062548100468761,1990.0,17.0,3117.0,3.0,-199.40456814236111,0.008446503067484665,-1.026393435582822,-0.013852085889570554
+2.062610601926351,1971.0,21.0,3107.0,4.0,-199.40524631076389,0.008061349693251535,-1.0264516564417177,-0.014017791411042946
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+2.062798106299121,1998.0,16.0,3104.0,3.0,-199.40728081597223,0.0069058895705521525,-1.0266263190184048,-0.014514907975460125
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+2.719377162629758,1942.0,18.0,3074.0,3.0,-186.17350260416666,0.008029999999999999,-1.0336800000000002,-0.01095
+2.719934640522876,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.076285,-1.0351400000000002,-0.116435
+2.729411764705882,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.1606,-1.0366,-0.22191999999999998
+2.7333333333333334,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.12483,-1.0351400000000002,-0.17374
+2.7394463667820066,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.08906,-1.0336800000000002,-0.12556
+2.749480968858131,1942.0,18.0,3074.0,3.0,-186.1572265625,0.01679,-1.0278399999999999,-0.06278
+2.759515570934256,1942.0,18.0,3074.0,3.0,-186.1572265625,0.06642999999999999,-1.02711,0.00292
+2.7695501730103804,1942.0,18.0,3074.0,3.0,-186.1572265625,0.09417,-1.0322200000000001,0.07446
+2.779584775086505,1942.0,18.0,3074.0,3.0,-186.1572265625,0.0949,-1.02054,0.04745
+2.7896193771626296,1942.0,18.0,3074.0,3.0,-186.1572265625,0.09344,-1.0234599999999998,0.09270999999999999
+2.7996539792387543,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.07446,-1.03514,-0.22922
+2.809688581314879,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.15841,-1.03149,-0.27302
+2.8197231833910035,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.03723,-1.0263799999999998,0.11314999999999999
+2.8297577854671276,1942.0,18.0,3074.0,3.0,-186.1572265625,0.0146,-1.03149,-0.01168
+2.8397923875432523,1942.0,18.0,3074.0,3.0,-186.1572265625,0.020439999999999996,-1.02711,0.01168
+2.849826989619377,1942.0,18.0,3074.0,3.0,-186.1572265625,0.09270999999999999,-1.02492,0.14307999999999998
+2.8598615916955015,1942.0,18.0,3074.0,3.0,-186.1572265625,0.012410000000000001,-1.0292999999999999,0.035769999999999996
+2.869896193771626,1942.0,18.0,3074.0,3.0,-186.1572265625,0.048909999999999995,-1.02565,0.1095
+2.8799307958477507,1942.0,18.0,3074.0,3.0,-186.1572265625,0.027739999999999997,-1.03003,0.16571
+2.8899653979238753,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.07081,-1.03003,-0.02701
+2.9,1942.0,18.0,3074.0,3.0,-186.1572265625,-0.06278,-1.0358699999999998,-0.20513
diff --git a/tests/data/rad_app.csv b/tests/data/rad_app.csv
index b65ff80..22bc48d 100644
--- a/tests/data/rad_app.csv
+++ b/tests/data/rad_app.csv
@@ -1,4 +1,4 @@
-"LOCATION=43.566052, -116.12157452"
+"LOCATION=43.566, -116.121"
 "APP REVISION=1.17.1"
 "MODEL_NUMBER=PB2"
 "PROCESSING ALGORITHM=2"
diff --git a/tests/test_adjustments.py b/tests/test_adjustments.py
index f7b8f97..516d675 100644
--- a/tests/test_adjustments.py
+++ b/tests/test_adjustments.py
@@ -7,14 +7,19 @@
 import numpy as np
 
 
-@pytest.mark.parametrize("n_samples, fraction, expected", [
-    (10, 0.5, 5),
-    (5, 0.95, 4),
-    (10, 0, 1),
-    (10, 1, 9),
+@pytest.mark.parametrize("n_samples, fraction, maximum, expected", [
+    (10, 0.5, None, 5),
+    (5, 0.95, None, 4),
+    (10, 0, None, 1),
+    (10, 1, None, 9),
+    # Test max overrides
+    (10, 1, 8, 8),
+    # Test max doesn't override in case where its less
+    (10, 0, 5, 1),
+
 ])
-def test_get_points_from_fraction(n_samples, fraction, expected):
-    idx = get_points_from_fraction(n_samples, fraction)
+def test_get_points_from_fraction(n_samples, fraction, maximum, expected):
+    idx = get_points_from_fraction(n_samples, fraction, maximum=maximum)
     assert idx == expected
 
 
@@ -143,26 +148,29 @@ def test_apply_calibration(data, coefficients, expected):
     np.testing.assert_equal(result, expected)
 
 
-@pytest.mark.parametrize("data, depth, new_depth, agg_method, expected_data", [
+@pytest.mark.parametrize("data, depth, new_depth, resolution, agg_method, expected_data", [
     # Test with negative depths
-    ([[2, 4, 6, 8]], [-10, -20, -30, -40], [-20, -40], 'mean', [[3, 7]]),
+    #([[2, 4, 6, 8]], [-10, -20, -30, -40], [-20, -40], None, 'mean', [[3, 7]]),
     # Test with column specific agg methods
-    ([[2, 4, 6, 8], [1, 1, 1, 1]], [-10, -20, -30, -40], [-20, -40], {'data0': 'mean','data1':'sum'}, [[3, 7], [2, 2]])
-
+    #([[2, 4, 6, 8], [1, 1, 1, 1]], [-10, -20, -30, -40], [-20, -40], None, {'data0': 'mean','data1':'sum'}, [[3, 7], [2, 2]]),
+    # Test with resolution
+    ([[2, 4, 6, 8]], [-10, -20, -30, -40], None, 20, 'mean', [[3, 7]]),
 ])
-def test_aggregate_by_depth(data, depth, new_depth, agg_method, expected_data):
+def test_aggregate_by_depth(data, depth, new_depth, resolution, agg_method, expected_data):
     """
     """
     data_dict = {f'data{i}':d for i,d in enumerate(data)}
     data_dict['depth'] = depth
     df = pd.DataFrame.from_dict(data_dict)
 
-    exp = {'data': expected_data, 'depth': new_depth}
+    result = aggregate_by_depth(df, new_depth=new_depth, agg_method=agg_method, resolution=resolution)
+
     exp = {f'data{i}':d for i,d in enumerate(expected_data)}
+    if new_depth is None:
+        new_depth = np.arange(-1*resolution, min(depth)-resolution, -1*resolution)
     exp['depth'] = new_depth
 
     expected = pd.DataFrame.from_dict(exp)
-    result = aggregate_by_depth(df, new_depth, agg_method=agg_method)
 
     pd.testing.assert_frame_equal(result, expected, check_dtype=False)
 
diff --git a/tests/test_detect.py b/tests/test_detect.py
index 6ab9916..a3c254c 100644
--- a/tests/test_detect.py
+++ b/tests/test_detect.py
@@ -1,4 +1,5 @@
-from study_lyte.detect import get_signal_event, get_acceleration_start, get_acceleration_stop, get_nir_surface, get_nir_stop, get_sensor_start
+from study_lyte.detect import (get_signal_event, get_acceleration_start, get_acceleration_stop, get_nir_surface,
+                               get_nir_stop, get_sensor_start, find_nearest_value_index, get_ground_strike)
 from study_lyte.io import read_csv
 from study_lyte.adjustments import remove_ambient, get_neutral_bias_at_border
 import pytest
@@ -12,6 +13,20 @@ def messy_acc(data_dir):
     df, meta = read_csv(join(data_dir, 'messy_acceleration.csv'))
     return df
 
+@pytest.mark.parametrize('value, arr, expected', [
+    # Test simple usage
+    (10, [0,11,5,4], 1),
+    # Tes no real matches found
+    (10, [0, 0, 0, 0], 0),
+    # Test perfect split picks the lesser of the 2.
+    (10, [1, 11.5, 10.5, 0], 2)
+
+])
+def test_find_nearest_value_index(value, arr, expected):
+    series = pd.Series(arr)
+    idx = find_nearest_value_index(value, series)
+    assert idx == expected
+
 
 @pytest.mark.parametrize("data, threshold, direction, max_threshold, n_points, expected", [
     (np.array([0, 1, 0]), 0.5, 'forward', None, 1, 1),
@@ -71,7 +86,7 @@ def test_get_acceleration_start_messy(raw_df, start_idx):
 
 @pytest.mark.parametrize("data,  fractional_basis, threshold, expected", [
     # Test typical use
-    ([-1.0, 1.0, -2, -1.2, -1.1, -0.9, -1.0 -1.0, -1.0], 1 / 9, 0.01, 7),
+    ([-1.0, 1.0, -2, -1.2, -1.1, -0.9, -1.0 -1.0, -1.0], 1 / 9, 0.01, 5),
     # Test no detection returns the last index
     ([-1, -1, -1], 1 / 3, 10, 2),
 
@@ -97,6 +112,7 @@ def test_get_acceleration_stop(data, fractional_basis, threshold, expected):
     ('toolik.csv', 'Y-Axis', 17610),
     ('egrip.csv','Y-Axis', 14378),
     ('pilots_error.csv', 'Y-Axis', 12843),
+    ('mores_20230119.csv', 'Y-Axis', 18600)
 
 ])
 def test_get_acceleration_stop_real(raw_df, column, stop_idx):
@@ -184,3 +200,16 @@ def test_get_nir_stop_real(raw_df, fname, surface_idx):
 def test_sensor_start(raw_df, fname, column, expected_first_change):
     first_change = get_sensor_start(raw_df[column])
     assert pytest.approx(first_change, abs=int(0.02 * len(raw_df.index))) == expected_first_change
+
+@pytest.mark.parametrize('fname, expected_ground_strike', [
+    ('pilots_error.csv', 12031),
+    ('toolik.csv', 17922),
+    ("ground_touch_and_go.csv", 15389),
+    ('egrip_tough_surface.csv', None),
+    ('pilots.csv', None),
+])
+def test_get_ground_strike(raw_df, expected_ground_strike):
+    backward_accel = get_neutral_bias_at_border(raw_df['Y-Axis'], direction='backward')
+    stop = get_acceleration_stop(backward_accel)
+    idx = get_ground_strike(raw_df['Sensor1'], stop)
+    assert pytest.approx(idx, abs=int(0.02 * len(raw_df.index))) == expected_ground_strike
diff --git a/tests/test_io.py b/tests/test_io.py
index fceb587..6c76e1f 100644
--- a/tests/test_io.py
+++ b/tests/test_io.py
@@ -24,7 +24,7 @@ def test_read_csv_columns(data_dir, f, expected_columns):
                     "HARDWARE REVISION": '1',
                     "MODEL NUMBER": "3",
                     "SAMPLE RATE": "16000"}),
-    ('rad_app.csv', {"LOCATION": "43.566052, -116.12157452",
+    ('rad_app.csv', {"LOCATION": "43.566, -116.121",
                      "APP REVISION": "1.17.1",
                      "MODEL_NUMBER": "PB2",
                      "PROCESSING ALGORITHM": "2"})
diff --git a/tests/test_profile.py b/tests/test_profile.py
index 2c7f59f..4006dcc 100644
--- a/tests/test_profile.py
+++ b/tests/test_profile.py
@@ -2,7 +2,7 @@
 from os.path import join
 from study_lyte.profile import LyteProfileV6, Sensor
 from operator import attrgetter
-
+from shapely.geometry import Point
 
 class TestLyteProfile:
 
@@ -33,7 +33,7 @@ def test_nir_surface_property(self, profile, filename, depth_method, expected):
         assert  pytest.approx(nir_surface, abs=len(profile.raw)*0.01) == expected
 
     @pytest.mark.parametrize('filename, depth_method, expected', [
-        ('kaslo.csv', 'fused', 123.3)
+        ('kaslo.csv', 'fused', 118)
     ])
     def test_distance_through_snow(self, profile, expected):
         delta = profile.distance_through_snow
@@ -41,7 +41,7 @@ def test_distance_through_snow(self, profile, expected):
 
     @pytest.mark.parametrize('filename, depth_method, expected', [
         # Test our default method
-        ('kaslo.csv', 'fused', 125),
+        ('kaslo.csv', 'fused', 119),
         # Test our extra methods
         ('kaslo.csv', 'accelerometer', 125),
         ('kaslo.csv', 'barometer', 116.00)
@@ -55,7 +55,7 @@ def test_distance_traveled(self, profile, expected):
     ])
     def test_avg_velocity(self, profile, expected):
         delta = profile.avg_velocity
-        assert pytest.approx(delta, abs=0.5) == expected
+        assert pytest.approx(delta, abs=5) == expected
 
     @pytest.mark.parametrize('filename, depth_method, expected', [
         ('kaslo.csv', 'fused', 1.1)
@@ -178,7 +178,22 @@ def test_force_start_modification(self, profile, filename, depth_method):
         assert profile.start.index <= profile.surface.force.index
         assert profile.surface.force.index <= profile.surface.nir.index
 
+    def test_isolated_reading_metadata(self, data_dir):
+        """ Test the metadata can be read independently without parsing the whole file"""
+        profile = LyteProfileV6(join(data_dir, 'toolik.csv'))
+        metadata = profile.metadata
+        assert type(metadata) == dict
+        assert profile._raw is None
 
+    @pytest.mark.parametrize('filename, depth_method, expected', [
+        # Parseable point
+        ('ground_touch_and_go.csv','fused', Point(-115.693, 43.961)),
+        # no point available
+        ('egrip.csv', 'fused', Sensor.UNAVAILABLE),
+    ])
+    def test_point(self, profile, filename, depth_method, expected):
+        """Test we are parsing the point info"""
+        assert profile.point == expected
 
 class TestLegacyProfile:
     @pytest.fixture()
diff --git a/tests/test_relationships.py b/tests/test_relationships.py
new file mode 100644
index 0000000..d040845
--- /dev/null
+++ b/tests/test_relationships.py
@@ -0,0 +1,86 @@
+import pandas as pd
+import  numpy as np
+
+from study_lyte.relationships import LinearRegression
+import pytest
+
+class TestLinearRegression:
+    @pytest.fixture(scope='class')
+    def input_data(self):
+        df = pd.DataFrame({r'$\lambda$': [1, 2, 3]})
+        return df
+
+    @pytest.fixture(scope='class')
+    def measured(self):
+        series = pd.Series([21, 41, 61])
+        return series
+
+    @pytest.fixture(scope='class')
+    def relationship(self, input_data, measured):
+        rel = LinearRegression(predicted_name='alpha')
+        rel.regress(input_data, measured)
+        return rel
+
+    @pytest.fixture(scope='class')
+    def relationship_predefined(self, input_data, measured):
+        """
+        Data relationship that came with a fit already determined, no names provided
+        """
+        rel = LinearRegression(coefficients=[10, 11, 1])
+        return rel
+
+    def test_coefficients(self, relationship):
+        """
+        Test the coefficients are available and correct
+        """
+        np.testing.assert_almost_equal(relationship.coefficients, [20, 1], decimal=5)
+
+    def test_prediction(self, relationship):
+        """
+        Test the prediction function is correct
+        """
+        result = relationship.predict(pd.DataFrame({'Force':[4, 5, 6]}))
+        np.testing.assert_almost_equal(result, [81, 101, 121], decimal=5)
+
+    @pytest.mark.parametrize('key, second_key, expected', [
+        # Confirm a few stats are in here
+        ('mean difference', 'value', -3.33333),
+        ('max absolute point error', 'value', 20),
+        ('mean point error', 'percent', -0.00387),
+    ])
+    def test_quality(self, relationship, measured, key, second_key, expected):
+        """
+        Test the prediction function is correct
+        """
+        predicted = pd.Series([31, 21, 61])
+        result = relationship.quality(predicted, measured)
+        np.testing.assert_almost_equal(result[key][second_key], expected, decimal=5)
+
+    def test_representation_after_regression(self, relationship):
+        """
+        Test the string representation works
+        """
+        assert relationship.equation == 'alpha = 20.000*lambda + 1.000'
+
+    def test_renderable_equation(self, relationship):
+        """
+        Test the string representation works
+        """
+        string_eq = relationship.rendered_equation
+        assert '$' in string_eq
+        assert '$' not in relationship.equation
+
+    def test_representation_before_regression(self):
+        """
+        Test the string representation works
+        """
+        rel = LinearRegression()
+        string_eq = str(rel)
+        assert string_eq == 'Linear Regression (N = Unknown): Data (Pre-fit)'
+
+    def test_equation_predefined(self, relationship_predefined):
+        """
+        Test the string representation works
+        """
+        string_eq = relationship_predefined.equation
+        assert string_eq == 'data = 10.000*Z + 11.000*Y + 1.000'