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-rw-r--r--sem4/hpp/miniproject/multiproc.py137
-rw-r--r--sem4/hpp/miniproject/naive.py30
-rw-r--r--sem4/hpp/miniproject/optimised.py66
-rw-r--r--sem4/hpp/miniproject/runner.py82
4 files changed, 188 insertions, 127 deletions
diff --git a/sem4/hpp/miniproject/multiproc.py b/sem4/hpp/miniproject/multiproc.py
index be39326..96fe788 100644
--- a/sem4/hpp/miniproject/multiproc.py
+++ b/sem4/hpp/miniproject/multiproc.py
@@ -1,107 +1,88 @@
-#!/usr/bin/env python3
-
import numpy as np
-import matplotlib.pyplot as plt
-import time
import multiprocessing as mp
-from multiprocessing import RawArray
+
+# Local import
+from optimised import numpylota
# c-mesh limits
limitre = ( -2, 1 )
limitim = ( -1.5, 1.5 )
+def createmangelctx(pre, pim, T, l, savez):
+ """
+ Calculates the context used when calculating mangelbrot
-def worker(gridchunk, s, step, T, l):
- global rs
- # Preallocate z array
- rschunk = rs[s : s + step]
+ :param pre: Number of real numbers in cmatrix
+ :param pim: Number of imaginary numbers in cmatrix
+ :param T: Mangelbrot threshold
+ :param l: Iterations
+ """
+ sre = ( limitre[1] - limitre[0] ) / (pre-1)
- z = np.zeros(rschunk.shape)
- print(f"rschunk.shape: {rschunk.shape}, gridchunk.shape: {gridchunk.shape}, T: {T}, l: {l}")
+ ctx = (sre, pim, T, l, savez)
+
+ return ctx
- # Calculate ι for all complex numbers
- for i in range(l):
- # This will generate warnings for some of the values rising above T.
- # Because these values are above T they are not used, thus the warnings
- # can be ignored
- z = z*z + gridchunk
+def mangelstep(ctx, re):
+ """
+ Calculates a single mangelbrot row.
+
+ :param ctx: Context containing information about mangelbrot
+ :param re: Row to calculate
+ """
- # This will generate 1 in all the places
- # where z < T and zeros elsewhere
- below = (np.abs(z) < T)
+ # Unpack context
+ (sre, pim, T, l, savez) = ctx
- # Add this to the result
- # Because the ones that pass T are 0
- # they will stop counting.
- #
- # If a specific z never reaches >= T its value in rs will
- # be l
- rschunk += below
+ # Create c-mesh row
+ im = np.linspace(limitim[0], limitim[1], pim, dtype=complex)
+ np.add(1j * im, limitre[0] + sre * re, im)
- np.divide(rschunk, l, out=rschunk)
+ # Calculate ι
+ rs = numpyiota(im, T, l, savez)
+ if savez:
+ return rs
+ else:
+ # It takes some time to unpack a list of tuples
+ # So if no savez do not return a tuple
+ return rs[0]
-def mangel(pre, pim, T, l, workers):
+def mangel(pre, pim, T, l, savez):
"""
- Calculate the mangelbrot image with multiple processes
+ Calculate the mangelbrot image
(pre, pim) discribes the image size. Use T and l to tune the mangelbrot
-
- This will split the image in horizontal parts and distribute it
- between the workers.
- Because the result array is row major, data will be nicely together if
- the workers work with rows not columns.
-
- Pre must be devisible by workers.
-
- The result is saved in rs. Sorry couln't get numpy references through to the process as arguments
+ This function uses the global variables limitre and limitim to determine
+ the c-mesh range.
:param pre: Number of real numbers used
:param pim: Number of imaginary numbers
:param T: Mangelbrot threshold
:param l: Iterations
- :param workers: Number of workers.
+ :param savez: Return z as the second element of returned tuple
"""
- # Used to calculate c-mesh
- re = np.linspace(limitre[0], limitre[1], pre)
- im = np.linspace(limitim[0], limitim[1], pim)
-
- # Calculate c-mesh
- grid = np.add.outer(re, 1j * im)
-
- # Calculate the partition variables
- step = int(pre / workers)
-
-
- # Loop chunks and start the workers
- wl = []
- for s in range(0, pre, step):
- gridchunk = grid[s : s + step]
- p = mp.Process(target=worker, args=(gridchunk, s, step, T, l))
- wl.append(p)
- p.start()
-
- # Wait for them to be done
- for p in wl:
- p.join()
+ ctx = createmangelctx(pre, pim, T, l, savez)
- return rs
+ # Number of processes
+ procs = mp.cpu_count()
-rs = np.full((500, 500), 0.5)
+ pool = mp.Pool(processes=procs)
-start = time.time()
-arr = mangel(500, 500, 2, 100, 1)
-end = time.time()
+ args = ((ctx, i) for i in range(pre))
+ result = pool.starmap_async(mangelstep, args)
+ pool.close()
+ pool.join()
-plt.imshow(arr, cmap=plt.cm.hot, vmin=0, vmax=1)
-plt.savefig("mult.png")
+ result = result.get()
+ if savez:
+ z = [None] * pre
+ rs = [None] * pre
-print(f"Took {end - start} seconds")
-"""
- p = mp.Process(target=worker, args=(rs[s:s + step], grid[s:s + step], T, l))
- wl.append(p)
- p.start()
+ # Unzip rs
+ for i, r in enumerate(result):
+ rs[i] = r[0]
+ z[i] = r[1]
- # Wait for them to be done
- for p in wl:
- p.join()
-"""
+ return (np.vstack(rs), np.vstack(z))
+ else:
+ return (np.vstack(result), None)
diff --git a/sem4/hpp/miniproject/naive.py b/sem4/hpp/miniproject/naive.py
index 765878a..24e366d 100644
--- a/sem4/hpp/miniproject/naive.py
+++ b/sem4/hpp/miniproject/naive.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import time
@@ -7,9 +6,10 @@ import time
limitre = ( -2, 1 )
limitim = ( -1.5, 1.5 )
-def lota(c, T, l):
+def iota(c, T, l):
"""
Implement the ι function used in mangelbrot
+ Also devides by l
:param c: Complex number from the c-mesh
:param T: Mangelbrot threshold
@@ -22,12 +22,12 @@ def lota(c, T, l):
# Check if we found or z
if np.abs(z) > T:
- return i
+ return (i / l, z)
# If we did not find z, use l
- return l
+ return (l / l, z)
-def mangel(pre, pim, T, l):
+def mangel(pre, pim, T, l, savez):
"""
Calculate the mangelbrot image
(pre, pim) discribes the image size. Use T and l to tune the mangelbrot
@@ -38,10 +38,12 @@ def mangel(pre, pim, T, l):
:param pim: Number of imaginary numbers
:param T: Mangelbrot threshold
:param l: Iterations
+ :param savez: Return z as the second element of returned tuple
"""
# Preallocate result array
rs = np.zeros((pre, pim))
+ z = np.empty((pre, pim), dtype=complex)
# Calculate scaling variables
sre = ( limitre[1] - limitre[0] ) / (pre-1)
@@ -54,17 +56,9 @@ def mangel(pre, pim, T, l):
c = limitre[0] + limitim[0] * 1j + sre * re + 1j * sim * im
# Calculate the ι
- rs[re,im] = lota(c, T, l) / l
+ (rs[re,im], z[re, im]) = iota(c, T, l)
- return rs
-
-
-start = time.time()
-arr = mangel(500, 500, 2, 100)
-end = time.time()
-
-plt.imshow(arr, cmap=plt.cm.hot, vmin=0, vmax=1)
-plt.savefig("test.png")
-plt.savefig("test.pdf")
-
-print(f"Took {end - start} seconds")
+ if savez:
+ return (rs, z)
+ else:
+ return (rs, None)
diff --git a/sem4/hpp/miniproject/optimised.py b/sem4/hpp/miniproject/optimised.py
index 2d128c9..299d25e 100644
--- a/sem4/hpp/miniproject/optimised.py
+++ b/sem4/hpp/miniproject/optimised.py
@@ -1,5 +1,3 @@
-#!/usr/bin/env python3
-
import numpy as np
import matplotlib.pyplot as plt
import time
@@ -8,33 +6,23 @@ import time
limitre = ( -2, 1 )
limitim = ( -1.5, 1.5 )
-def mangel(pre, pim, T, l):
+def numpyiota(grid, T, l, savez):
"""
- Calculate the mangelbrot image
- (pre, pim) discribes the image size. Use T and l to tune the mangelbrot
- This function uses the global variables limitre and limitim to determine
- the c-mesh range.
-
- :param pre: Number of real numbers used
- :param pim: Number of imaginary numbers
- :param T: Mangelbrot threshold
- :param l: Iterations
+ Calculates the ι using numpy arrays.
+ This works with both numpy.arrays and numpy.ndarrays
+ Also devides by l
+
+ :param grid: c-mesh. Shape will be used to make result
+ :param savez: Return z as the second element of returned tuple
"""
# Preallocate result array and z array
- rs = np.zeros((pre, pim))
- z = np.zeros((pre, pim))
-
- # Used to calculate c-mesh
- re = np.linspace(limitre[0], limitre[1], pre)
- im = np.linspace(limitim[0], limitim[1], pim)
-
- # Calculate c-mesh
- grid = np.add.outer(re, 1j * im)
+ rs = np.zeros(grid.shape)
+ z = np.zeros(grid.shape)
# Calculate ι for all complex numbers
for i in range(l):
# This will generate warnings for some of the values rising above T.
- # Because these values are above T they are not used, thus the warnings
+ # Because these values become NAN they are not used, thus the warnings
# can be ignored
z = z*z + grid
@@ -51,15 +39,31 @@ def mangel(pre, pim, T, l):
rs += below
rs /= l
-
- return rs
-if __name__ == "__main__":
- start = time.time()
- arr = mangel(500, 500, 2, 100)
- end = time.time()
+ if not savez:
+ z = None
+ return (rs, z)
- plt.imshow(arr, cmap=plt.cm.hot, vmin=0, vmax=1)
- plt.savefig("opt.png")
+def mangel(pre, pim, T, l, savez):
+ """
+ Calculate the mangelbrot image
+ (pre, pim) discribes the image size. Use T and l to tune the mangelbrot
+ This function uses the global variables limitre and limitim to determine
+ the c-mesh range.
+
+ :param pre: Number of real numbers used
+ :param pim: Number of imaginary numbers
+ :param T: Mangelbrot threshold
+ :param l: Iterations
+ :param savez: Return z as the second element of returned tuple
+ """
+
+ # Used to calculate c-mesh
+ re = np.linspace(limitre[0], limitre[1], pre)
+ im = np.linspace(limitim[0], limitim[1], pim)
+
+ # Calculate c-mesh
+ grid = np.add.outer(re, 1j * im)
- print(f"Took {end - start} seconds")
+ # Calculate ι
+ return numpyiota(grid, T, l, savez)
diff --git a/sem4/hpp/miniproject/runner.py b/sem4/hpp/miniproject/runner.py
new file mode 100644
index 0000000..1565bd5
--- /dev/null
+++ b/sem4/hpp/miniproject/runner.py
@@ -0,0 +1,82 @@
+#!/usr/bin/env python3
+
+import matplotlib.pyplot as plt
+import argparse
+import os.path as path
+import numpy as np
+import time
+from pathlib import Path
+from PIL import Image
+import warnings
+import h5py
+
+# Many of the implementations overflow some of the values
+# This creates warnings which can be ignored
+warnings.simplefilter("ignore")
+
+# Implementations
+impls = ["naive", "optimised", "multiproc"]
+
+parser = argparse.ArgumentParser(description="runs the different mangelbrot implementations")
+parser.add_argument("impl", help="which implementation", default='all', choices=impls + ["all"], nargs='*')
+parser.add_argument("--numreal", "--nr", type=int, help="number of real numbers", default=500)
+parser.add_argument("--numimag", "--ni", type=int, help="number of imaginary numbers", default=500)
+parser.add_argument("--iterations", "-i", type=int, help="mangelbrot iterations", default=100)
+parser.add_argument("--threshold", "-t", type=int, help="mangelbrot threshold", default=2)
+parser.add_argument("--outputfolder", "-o", help="output folder", default='.')
+parser.add_argument("--createpng", help="create png images", action="store_true")
+parser.add_argument("--skipz", "-z", help="do not export z", action="store_true")
+
+args = parser.parse_args()
+
+# If no implementations are specified run all
+if args.impl == "all" or "all" in args.impl:
+ args.impl = impls
+
+def runtest(mangel, name):
+ """
+ Run test on specified mangel function.
+ `mangel` function must be of form
+
+ ```
+ mangel(pre, pim, T, l)
+ ```
+
+ Uses the global args for options.
+ """
+
+ # Run mangel and measure runtime
+ start = time.time()
+ (rs, z) = mangel(args.numreal, args.numimag, args.threshold, args.iterations, not args.skipz)
+ end = time.time()
+
+ plt.imshow(rs, cmap=plt.cm.hot, vmin=0, vmax=1)
+ plt.savefig(path.join(args.outputfolder, name + ".pdf"))
+ if args.createpng:
+ # Convert o simple b/w image
+ formatted = (rs * 255).astype('uint8')
+
+ img = Image.fromarray(formatted, mode='L')
+ img.save(path.join(args.outputfolder, name + ".png"))
+
+ # Save data as h5py
+ h5file = h5py.File(path.join(args.outputfolder, name + ".h5"), "w")
+ h5file.create_dataset("result", data=rs)
+ if not args.skipz:
+ h5file.create_dataset("z", data=z)
+ h5file.close()
+
+ return end - start
+
+# Make sure output folder exists
+Path(args.outputfolder).mkdir(parents=True, exist_ok=True)
+
+print(f"Running implementations {args.impl}")
+
+for impl in args.impl:
+ # Import module
+ m = __import__(impl)
+
+ print(f"Running {impl}")
+ dur = runtest(m.mangel, impl)
+ print(f"{impl} took {dur} seconds")