Added files from local to remote

run.py

+import os
+import re
+import warnings
+from collections import defaultdict
+
+import numpy as np
+import matplotlib.pyplot as plt
+from tqdm import tqdm
+
+from measure import measure_cumulative_volume, measure_cumulative_points
+
+def parse_params(path):
+    with open(os.path.join(path, 'params.txt')) as f:
+        lines = f.readlines()
+
+    coords = []
+    thickness = []
+
+    for line in lines:
+        if 'origin' in line:
+            coords = [float(x) for x in re.findall('-?\d+\.?[0-9]*', line)]
+        if 'thickness' in line:
+            thickness = [float(x) for x in re.findall('-?\d+\.?[0-9]*', line)]
+
+    if len(coords) != 3:
+        print(f"found {len(coords)} coordinates when looking for 'origin' in params.txt")
+    if len(thickness) != 1:
+        print(f"found {len(coords)} coordinates when looking for 'origin' in params.txt")
+
+    thickness = thickness[0]
+
+    return coords, thickness
+
+def load_contours(path):
+    contour_dir = os.path.join(path, 'domain_contours')
+    file_fnames = os.listdir(contour_dir)
+    z_values = [float(file_fname[2:-4]) for file_fname in file_fnames]
+    z_values, file_fnames = zip(*sorted(zip(z_values, file_fnames)))
+    contours = []
+
+    for file_fname, z in zip(file_fnames, z_values):
+        X = np.loadtxt(os.path.join(contour_dir, file_fname))
+        Xp = np.pad(X, ((0,1), (0,0)), mode='wrap')
+        contours.append((z, X))      
+
+    return contours
+
+
+def load_points(path):
+    point_dirs = [os.path.join(path, path_name) for path_name in os.listdir(path) if path_name.startswith('points_marker_')]
+    marker_names = [dir_name.split('points_marker_')[-1] for dir_name in point_dirs]
+
+    points = defaultdict(list)
+    for point_dir, marker_name in zip(point_dirs, marker_names):
+        file_fnames = os.listdir(point_dir)
+        z_values = [float(file_fname[2:-4]) for file_fname in file_fnames]
+        z_values, file_fnames = zip(*sorted(zip(z_values, file_fnames)))
+        for file_fname, z in zip(file_fnames, z_values):
+            X = np.loadtxt(os.path.join(point_dir, file_fname))
+            points[marker_name].append((z, X))            
+
+    return points
+
+def write_csv(path, R, dP, dV):
+
+    intdP = dP[1:] - dP[:-1]
+    intdV = dV[1:] - dV[:-1]
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        Dens = dP / dV
+        intDens = intdP / intdV
+
+    with open(path, 'w') as f:
+        f.write(','.join(['Cummulative Reading','','','','','Interval Reading\n']))
+        f.write(','.join(['Distance','Point Counts','Volume (mu^3)','Density (n/mu^3)','','Interval start (mu)',
+                          'Interval end (mu)','Point Counts (n)','Volume (mu^3)','Density (n/mu^3)\n']))
+        for i0,i1,a,b,c,d,e,v in zip(R[:-1], R[1:], dP, dV, Dens, intdP, intdV, intDens):
+            f.write(f'{i0},{a},{b},{c},,{i0},{i1},{d},{e},{v}\n')
+
+def run(base_dir):
+
+    R = np.arange(0, 3001, 125)
+
+    output_dir = 'output'
+    os.makedirs(output_dir, exist_ok=True)
+
+    for experiment in tqdm(os.listdir(base_dir), desc='experiment'):
+        for reading in os.listdir(os.path.join(base_dir, experiment)):
+            #if reading != '7566':
+            #    continue
+            data_dir = os.path.join(base_dir, experiment, reading)
+            origin, thickness = parse_params(data_dir)
+            
+            contours = sorted(load_contours(data_dir))
+            points = load_points(data_dir)
+            for marker in points.keys():
+                all_points = sorted(points[marker])
+                dV = []
+                dP = []
+                for sec_contour, sec_points in zip(contours, all_points):
+                    if sec_contour[0] != sec_points[0]:
+                        raise ValueError('z-coordinate misalignment, does points and contour have corresponding z-value')
+                    z, P = sec_contour
+                    dV.append(measure_cumulative_volume(z, P, thickness, origin, R))
+                    z, X = sec_points
+                    dP.append(measure_cumulative_points(z, X, thickness, origin, R))
+                
+                dP = np.sum(dP, axis=0)
+                dV = np.sum(dV, axis=0)
+
+                fname = f'{experiment}_{reading}_{marker}.csv'
+                path = os.path.join(output_dir, fname)
+
+                write_csv(path, R, dP, dV)
+
+if __name__ == '__main__':
+    base_dir = 'data'
+    run(base_dir)
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