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import csv
import math
import os
import re
from collections import deque
import matplotlib.pyplot as plot
def load(directory):
def _read(iterable):
for x, y in iterable:
yield float(x), float(y)
def _load(filename):
with open(filename) as fd:
reader = csv.reader(fd)
return list(_read(reader))
def _files(directory):
for file in os.listdir(directory):
match = re.match(r"SWI_(-?\d+)\.csv", file)
if match:
yield int(match.group(1)), os.path.join(directory, file)
return [(x, _load(y)) for x, y in sorted(_files(directory), key=lambda x: x[0])]
def look_downwards(data, x, start):
for i in range(start, 0, -1):
if data[i - 1][0] < x:
break
else:
raise IndexError
return i - 1
def look_upwards(data, x, start):
for i in range(start, len(data)):
if data[i + 1][0] > x:
break
else:
raise IndexError
return i
def find_segment(data, x):
width = data[-1][0] - data[0][0]
relative = x - data[0][0]
candidate = math.floor(relative / width * len(data))
look = look_downwards if data[candidate][0] > x else look_upwards # May raise IndexError
candidate = look(data, x, candidate)
return candidate, candidate + 1
def find_boundary_curves(swis, x, y):
segments = deque()
for index, data in swis:
i, j = find_segment(data, x)
if data[i][1] > y and data[j][1] > y:
segments.append((index, data, i, j))
break
if data[i][1] < y and data[j][1] < y:
if segments:
segments.popleft()
segments.append((index, data, i, j))
if len(segments) == 3:
middle = segments[1][1]
run = middle[j][0] - middle[i][0]
if run == 0:
raise RuntimeError # tidy up dataset
slope = (middle[j][1] - middle[i][1]) / run
intercept = middle[j][1] - slope * middle[j][0]
value = slope * x + intercept
if value == y:
raise RuntimeError # Exactly on point; SWI == index
if value < y:
segments.popleft()
else:
segments.pop()
if len(segments) == 1:
raise RuntimeError # SWI == -10
return segments
def dist(x1, y1, x2, y2):
return math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
def calculate_swi(segments, x, y):
low = segments[0]
high = segments[1]
dist_to_low = min(dist(p[0], p[1], x, y) for p in (low[1][low[2]], low[1][low[2]]))
dist_to_high = min(dist(p[0], p[1], x, y) for p in (high[1][high[2]], high[1][high[2]]))
return dist_to_low / (dist_to_low + dist_to_high) * (high[0] - low[0]) + low[0]
swis = load("dataset")
def _swi(x, y): # dt, depth
segments = find_boundary_curves(swis, x, y)
return calculate_swi(segments, x, y)
def grid(start, end, steps):
step = (end - start) / steps
i = start
while i <= end:
yield i
i += step
C = []
X = list(grid(0, 40, 1000))
Y = list(grid(0, 50000, 1000))
for y_scaled in range(0, 1000):
y = y_scaled * 50
row = []
for x_scaled in range(0, 1000):
x = x_scaled / 25
try:
swi = _swi(x, y)
except (IndexError, RuntimeError):
swi = -10
row.append(swi)
C.append(row)
plot.pcolormesh(X, Y, C, cmap='viridis', vmin=-10, vmax=10, rasterized=True)
for _, data in swis:
plot.plot([x[0] for x in data], [x[1] for x in data])
plot.show()
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