HNSW breakdown index and scripts

benchmark/scripts/breakdownHNSW/OoOCommon.py

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+import csv
+import numpy as np
+import matplotlib.pyplot as plt
+import itertools as it
+import os
+
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+import pylab
+from matplotlib.font_manager import FontProperties
+from matplotlib.ticker import LogLocator, LinearLocator
+import os
+import pandas as pd
+import sys
+import matplotlib.ticker as mtick
+
+OPT_FONT_NAME = 'Helvetica'
+TICK_FONT_SIZE = 22
+LABEL_FONT_SIZE = 28
+LEGEND_FONT_SIZE = 30
+LABEL_FP = FontProperties(style='normal', size=LABEL_FONT_SIZE)
+LEGEND_FP = FontProperties(style='normal', size=LEGEND_FONT_SIZE)
+TICK_FP = FontProperties(style='normal', size=TICK_FONT_SIZE)
+
+MARKERS = (['*', '|', 'v', "^", "", "h", "<", ">", "+", "d", "<", "|", "", "+", "_"])
+# you may want to change the color map for different figures
+COLOR_MAP = (
+    '#B03A2E', '#2874A6', '#239B56', '#7D3C98', '#FFFFFF', '#F1C40F', '#F5CBA7', '#82E0AA', '#AEB6BF', '#AA4499')
+# you may want to change the patterns for different figures
+PATTERNS = (["////", "o", "", "||", "-", "//", "\\", "o", "O", "////", ".", "|||", "o", "---", "+", "\\\\", "*"])
+LABEL_WEIGHT = 'bold'
+LINE_COLORS = COLOR_MAP
+LINE_WIDTH = 3.0
+MARKER_SIZE = 15.0
+MARKER_FREQUENCY = 1000
+
+
+def editConfig(src, dest, key, value):
+    df = pd.read_csv(src, header=None)
+    rowIdx = 0
+    idxt = 0
+    for cell in df[0]:
+        # print(cell)
+        if (cell == key):
+            rowIdx = idxt
+            break
+        idxt = idxt + 1
+    df[1][rowIdx] = str(value)
+    df.to_csv(dest, index=False, header=False)
+
+
+def readConfig(src, key):
+    df = pd.read_csv(src, header=None)
+    rowIdx = 0
+    idxt = 0
+    for cell in df[0]:
+        # print(cell)
+        if (cell == key):
+            rowIdx = idxt
+            break
+        idxt = idxt + 1
+    return df[1][rowIdx]
+
+
+def draw2yLine(NAME, Com, R1, R2, l1, l2, m1, m2, fname):
+    fig, ax1 = plt.subplots(figsize=(10, 6.4))
+    lines = [None] * 2
+    # ax1.set_ylim(0, 1)
+    print(Com)
+    print(R1)
+    lines[0], = ax1.plot(Com, R1, color=LINE_COLORS[0], \
+                         linewidth=LINE_WIDTH, marker=MARKERS[0], \
+                         markersize=MARKER_SIZE
+                         #
+                         )
+
+    # #plt.show()
+    ax1.set_ylabel(m1, fontproperties=LABEL_FP)
+    ax1.set_xlabel(NAME, fontproperties=LABEL_FP)
+    # ax1.set_xticklabels(ax1.get_xticklabels())  # 设置共用的x轴
+    plt.xticks(rotation=0, size=TICK_FONT_SIZE)
+    plt.yticks(rotation=0, size=TICK_FONT_SIZE)
+    plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
+    ax2 = ax1.twinx()
+
+    # ax2.set_ylabel('latency/us')
+    # ax2.set_ylim(0, 0.5)
+    lines[1], = ax2.plot(Com, R2, color=LINE_COLORS[1], \
+                         linewidth=LINE_WIDTH, marker=MARKERS[1], \
+                         markersize=MARKER_SIZE)
+
+    ax2.set_ylabel(m2, fontproperties=LABEL_FP)
+    # ax2.vlines(192000, min(R2)-1, max(R2)+1, colors = "GREEN", linestyles = "dashed",label='total L1 size')
+    # plt.grid(axis='y', color='gray')
+
+    # style = dict(size=10, color='black')
+    # ax2.hlines(tset, 0, x2_list[len(x2_list)-1]+width, colors = "r", linestyles = "dashed",label="tset")
+    # ax2.text(4, tset, "$T_{set}$="+str(tset)+"us", ha='right', **style)
+
+    # plt.xlabel('batch', fontproperties=LABEL_FP)
+
+    # plt.xscale('log')
+    # figure.xaxis.set_major_locator(LinearLocator(5))
+    ax1.yaxis.set_major_locator(LinearLocator(5))
+    ax2.yaxis.set_major_locator(LinearLocator(5))
+    ax1.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    ax2.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    ax1.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    ax2.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    plt.legend(lines,
+               [l1, l2],
+               prop=LEGEND_FP,
+               loc='upper center',
+               ncol=1,
+               bbox_to_anchor=(0.55, 1.3
+                               ), shadow=False,
+               columnspacing=0.1,
+               frameon=True, borderaxespad=-1.5, handlelength=1.2,
+               handletextpad=0.1,
+               labelspacing=0.1)
+    plt.yticks(rotation=0, size=TICK_FONT_SIZE)
+    plt.tight_layout()
+
+    plt.savefig(fname + ".pdf")