Merge pull request #2 from kcwongaz/Refactor

Refactor

characteristics/loops/hist-chain.py

@@ -0,0 +1,91 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+from loop_helpers import *
+
+
+# --------------------------------------------------------------------------- #
+# Target datetime range to plot flight on; UTC 16:00 is HKT 00:00
+target_start = pd.to_datetime("2018-01-01 00:00", format=r"%Y-%m-%d %H:%M")
+target_end = pd.to_datetime("2018-12-31 23:59", format=r"%Y-%m-%d %H:%M")
+target_start_str = target_start.strftime(r"%Y%m%d_%H%M")
+target_end_str = target_end.strftime(r"%Y%m%d_%H%M")
+dstr = f"{target_start_str}-{target_end_str}"
+
+datadir = f"/home/kc/Research/air_traffic/data/redirection"
+savedir = f"/home/kc/Research/air_traffic/figures/2022-04-26"
+mode = 2
+
+plt.rcParams.update({
+    "font.family": "serif",
+    "font.sans-serif": ["Helvetica"]}
+)
+
+savefig = False
+
+
+# --------------------------------------------------------------------------- #
+
+chain = np.loadtxt(f"{datadir}/chain_all_{dstr}.txt")
+
+fig, ax = plt.subplots()
+
+
+edges = np.arange(-0.5, 16, 1)
+centers = (edges[:-1] + edges[1:]) / 2
+
+hist, _ = np.histogram(chain, bins=edges)
+print(hist)
+print(sum(hist))
+
+
+# --------------------------------------------------------------------------- #
+if mode == 1:
+    ax.bar(centers, hist, color="darkorange")
+    ax.set_xticks(centers)
+
+    for rect in ax.patches:
+        height = rect.get_height()
+        ax.annotate(f'{int(height)}', xy=(rect.get_x()+rect.get_width()/2, height),
+                    xytext=(0, 3), textcoords='offset points',
+                    ha='center', va='bottom', fontsize=8, color="darkorange")
+
+    # ax.set_ylim(0, 3500)
+    ax.set_xlabel("Length of Redirection Chain", fontsize=14)
+    ax.set_ylabel("Count", fontsize=14)
+
+    ax.set_title("Histogram of Redirection Chains (2017)", fontsize=16)
+
+    plt.tight_layout()
+
+    if savefig:
+        plt.savefig(f"{savedir}/hist_chains.png", dpi=300)
+    plt.show()
+
+
+# --------------------------------------------------------------------------- #
+elif mode == 2:
+
+    hist[1:-1] = hist[1:-1] - hist[2:]
+    print(np.sum(np.arange(len(hist)) * hist))
+
+    ax.bar(centers, hist, color="salmon")
+    ax.set_xticks(centers)
+
+    for rect in ax.patches:
+        height = rect.get_height()
+        ax.annotate(f'{int(height)}', xy=(rect.get_x()+rect.get_width()/2, height),
+                    xytext=(0, 3), textcoords='offset points',
+                    ha='center', va='bottom', fontsize=8, color="salmon")
+
+    # ax.set_ylim(0, 3500)
+    ax.set_xlabel("Length of Redirection Chain", fontsize=14)
+    ax.set_ylabel("Count", fontsize=14)
+
+    ax.set_title("Histogram of Unqiue Chains (2017)", fontsize=16)
+
+    plt.tight_layout()
+    if savefig:
+        plt.savefig(f"{savedir}/hist_unqiue_chains.png", dpi=300)
+    plt.show()

characteristics/loops/hist-time_saved.py

@@ -0,0 +1,112 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+from loop_helpers import *
+
+
+# --------------------------------------------------------------------------- #
+# Target datetime range to plot flight on; UTC 16:00 is HKT 00:00
+target_start = pd.to_datetime("2018-01-01 00:00", format=r"%Y-%m-%d %H:%M")
+target_end = pd.to_datetime("2018-12-31 23:59", format=r"%Y-%m-%d %H:%M")
+target_start_str = target_start.strftime(r"%Y%m%d_%H%M")
+target_end_str = target_end.strftime(r"%Y%m%d_%H%M")
+dstr = f"{target_start_str}-{target_end_str}"
+
+datadir = f"/home/kc/Research/air_traffic/data/redirection"
+savedir = f"/home/kc/Research/air_traffic/figures/2022-04-26"
+
+mode = 1
+
+plt.rcParams.update({
+    "font.family": "serif",
+    "font.sans-serif": ["Helvetica"]}
+)
+
+savefig = False
+
+# --------------------------------------------------------------------------- #
+
+if mode == 1:
+    ts = np.loadtxt(f"{datadir}/ts_all_{dstr}.txt")
+    print(len(ts))
+    ts = ts[np.nonzero(ts)]
+    print(len(ts))
+
+    fig, ax = plt.subplots()
+
+    bins = np.arange(0, 121, 1)
+    ax.hist(ts, bins=bins, color="royalblue", rwidth=0.8)
+    ax.set_xticks(np.arange(0, 121, 10))
+
+    ax.set_xlabel("Total Time Saved $S$ (min)", fontsize=14)
+    ax.set_ylabel("Count")
+    ax.set_title("Histogram of Total Time Saved (2017)", fontsize=16)
+
+    print("Max: ", np.max(ts))
+    print("Min: ", np.min(ts))
+    print("Mean: ", np.mean(ts))
+    print("SD: ", np.std(ts), np.std(ts, ddof=1))
+
+
+    plt.tight_layout()
+    if savefig:
+        plt.savefig(f"{savedir}/hist_s_{dstr}.png", dpi=300)
+    plt.show()
+
+
+elif mode == 2:
+    ts = np.loadtxt(f"{datadir}/ts1_all_{dstr}.txt")
+    ts = ts[np.nonzero(ts)]
+
+    fig, ax = plt.subplots()
+
+    bins = np.arange(0, 41, 1)
+    ax.hist(ts, bins=bins, color="mediumpurple", rwidth=0.8)
+    ax.set_xticks(np.arange(0, 41, 5))
+
+    ax.set_xlabel("First-step Time Saved $S_1$ (min)", fontsize=14)
+    ax.set_ylabel("Count")
+    ax.set_title("Histogram of First-step Time Saved (2017)", fontsize=16)
+
+    print("Max: ", np.max(ts))
+    print("Min: ", np.min(ts))
+    print("Mean: ", np.mean(ts))
+    print("SD: ", np.std(ts), np.std(ts, ddof=1))
+
+    plt.tight_layout()
+    if savefig:
+        plt.savefig(f"{savedir}/hist_s1_{dstr}.png", dpi=300)
+    plt.show()
+
+
+elif mode == 3:
+    ts = np.loadtxt(f"{datadir}/ts_all_{dstr}.txt")
+    ts = ts[np.nonzero(ts)]
+
+    fig, ax = plt.subplots()
+
+    bins = np.arange(0, 251, 5)
+    centers = (bins[:-1] + bins[1:]) / 2
+
+    hist, _ = np.histogram(ts, bins=bins)
+
+    ind = np.nonzero(hist)
+    hist = hist[ind]
+    centers = centers[ind]
+
+    ax.plot(centers, hist, marker="o", color="royalblue", lw=1)
+
+    # ax.set_xticks(np.arange(0, 121, 10))
+    ax.set_xscale("log")
+    ax.set_yscale("log")
+
+    ax.set_xlabel("Total Time Saved $S$ (min)", fontsize=14)
+    ax.set_ylabel("Count")
+    ax.set_title("Histogram of Total Time Saved (2017)", fontsize=16)
+
+    print("Max: ", np.max(ts))
+    plt.tight_layout()
+    if savefig:
+        plt.savefig(f"{savedir}/hist_s_logscale.png", dpi=300)
+    plt.show()