Add Test script and result for sort

Ten separate command files are placed in `sort/` directory. The test can
be run in parallel using GNU parallel.
```
$ cat jobs.sh | parallel --group --bar -j8
```
The resulting stats and plot can be foundin `sort/stats` and
`sort/plots`.

jobs.sh

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+./qtest -f sort/sort1.cmd
+./qtest -f sort/sort2.cmd
+./qtest -f sort/sort3.cmd
+./qtest -f sort/sort4.cmd
+./qtest -f sort/sort5.cmd
+./qtest -f sort/sort6.cmd
+./qtest -f sort/sort7.cmd
+./qtest -f sort/sort8.cmd

process_sort.py

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+import sys
+import os
+from dataclasses import dataclass
+import matplotlib.pyplot as plt
+import numpy as np
+
+@dataclass
+class Stats:
+    name: str
+    pattern: int
+    size: list[int]
+    time: list[int]
+    cmps: list[int]
+
+# Parse log file and return result lists for each type
+# Returns a dictionary with type name as key and Stats
+def process_file(file_name):
+    type = {}
+    try:
+        with open(file_name, "r") as file:
+            for line in file:
+                t, pattern, size, time, cmps = line.split()
+                if t not in type:
+                    type[t] = Stats(t,pattern,[],[],[])
+                type[t].size.append(size)
+                type[t].time.append(time)
+                type[t].cmps.append(cmps)
+    except FileNotFoundError:
+        print(f"Error: File '{file_name}' not found.")
+    except Exception as e:
+        print(f"An error occurred while processing '{file_name}': {e}")
+    return type
+pattern_dict = {1 : 'All random',
+                2 : 'Descending',
+                3 : 'Ascending',
+                4 : 'Ascend_3rand',
+                5 : 'Ascend_10_rand',
+                6 : 'Ascend_rand1%',
+                7 : 'Duplicates', 
+                8 : 'All_Equal'}
+
+def __plot(x, y, x_name, y_name, label, plot_name, file_name):
+    plt.figure(figsize=(10,6))
+    xticks = np.arange(0, 12000, 1000)
+    y_max = np.max(y)
+    step_size = 100
+    while y_max / step_size > 10:
+        step_size *= 10
+    yticks = np.arange(0, y_max + step_size, step_size)
+    plt.scatter(x, y, label=label, marker='+', s=15, alpha=0.8)
+    plt.xlabel(x_name)
+    plt.ylabel(y_name)
+    ax = plt.gca()
+    ax.set_xticks(xticks)
+    ax.set_yticks(yticks)
+    plt.xticks(rotation=30)
+    plt.title(plot_name)
+    plt.legend()
+    plt.savefig(file_name)
+    plt.close()
+
+def __plot_mixed(x, data, y_name, data_name, plot_name, file_name):
+    # Draw mixed figure
+    plt.figure(figsize=(10,6))
+    max = -1
+    for d,n in zip(data,data_name):
+        plt.scatter(x, d, label=n, marker='+', s=15, alpha=0.8)
+        if np.max(d) > max:
+            max = np.max(d)
+    xticks = np.arange(0, 12000, 1000)
+    y_max = max
+    step_size = 100
+    while y_max / step_size > 10:
+        step_size *= 10
+    yticks = np.arange(0, y_max + step_size, step_size)
+    # Set labels and title
+    plt.xlabel('Size')
+    plt.ylabel(y_name)
+    ax = plt.gca()
+    ax.set_xticks(xticks)
+    ax.set_yticks(yticks)
+    plt.xticks(rotation=30)
+    plt.title(plot_name)
+    plt.legend()
+    plt.savefig(file_name)
+    plt.close()
+
+def plot(result):
+    # Iterate through all sorting
+    size = 0
+    nameL = []
+    timeL = []
+    cmpsL = [] 
+    for d in result:
+        data=result[d]
+        plt.figure()
+        data = result[d]
+        pattern = data.pattern
+        # Convert to numpy array
+        size = np.array(data.size).astype(int)
+        time = np.array(data.time).astype(int)
+        cmps = np.array(data.cmps).astype(int)
+        timeL.append(time)
+        cmpsL.append(cmps)
+        nameL.append(data.name)
+
+        __plot(size, time, "Size", "Time", d, \
+               f'{data.name}sort {pattern_dict[int(pattern)]} -- Time', \
+               prefix + '/../plots/' + f'{data.name}_{pattern}_time.png')
+        __plot(size, cmps, "Size", "Comparisons", d, \
+               f'{data.name}sort {pattern_dict[int(pattern)]} -- Comparisons', \
+               prefix + '/../plots/' + f'{data.name}_{pattern}_cmps.png')
+    __plot_mixed(size, timeL, 'Size', nameL, \
+                f'Mixed {pattern_dict[int(pattern)]} -- Time', \
+                prefix + '/../plots/' + f'Mixed_{pattern}_time.png')
+    __plot_mixed(size, cmpsL, 'Size', nameL, \
+                f'Mixed {pattern_dict[int(pattern)]} -- Comparisons', \
+                prefix + '/../plots/' + f'Mixed_{pattern}_cmps.png')
+
+if __name__ == "__main__":
+    if(len(sys.argv) < 2):
+        print(f"Usage: python {sys.argv[0]} input_file1 input_file2 ...")
+        sys.exit()
+    input_files = sys.argv[1:]
+    for i in input_files:
+        prefix = os.path.dirname(i)
+        result = process_file(i)
+        print(f'Plotting {i}...')
+        plot(result)
+
+
+
+

sort/sort1.cmd

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+# Do sort test
+sorttestL 1 100 12000 100 sort/stats/sort1.log

sort/sort2.cmd

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+# Do sort test
+sorttestL 2 100 12000 100 sort/stats/sort2.log

sort/sort3.cmd

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+# Do sort test
+sorttestL 3 100 12000 100 sort/stats/sort3.log

sort/sort4.cmd

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+# Do sort test
+sorttestL 4 100 12000 100 sort/stats/sort4.log

sort/sort5.cmd

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+# Do sort test
+sorttestL 5 100 12000 100 sort/stats/sort5.log

sort/sort6.cmd

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+# Do sort test
+sorttestL 6 100 12000 100 sort/stats/sort6.log

sort/sort7.cmd

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+# Do sort test
+sorttestL 7 100 12000 100 sort/stats/sort7.log

sort/sort8.cmd

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+# Do sort test
+sorttestL 8 100 12000 100 sort/stats/sort8.log