update max speed acc trade off figure

README.md

@@ -125,6 +125,7 @@ Maximum 4 species 3 reactions, Example speed/accuracy trade off figure.
 ### Data
 * `paper/maximum_out_S4_R3/Bimol_1.speedtime` - Speed-accuracy trade off data
 * `paper/maximum_out_S4_R3/Bimol_1.lbs` - CRN file used
+*  paper/maximum_out_S4_R3/Bimol_1_tf10000.tsv - heatmap file 
 ### Code
 * `python paper/fig_max_speed_ac/fig_max_histo.py`
 
@@ -176,4 +177,4 @@ All CRNs shown in the paper are stored in a compressed format in the `Storage` d
 
 `python python/lbs_storage.py --crn_storage_file Storage\AMno11_S3_R3_CRNs.tsv -d AMno11_S3_R3 -r all`
 
-Alternatively, you can choose to decompress a single CRN by using its integer identifier as the argument for `r`.
+Alternatively, you can choose to decompress a single CRN by using its integer identifier as the argument for `r`.

paper/fig_max_speed_ac/fig_max_speed.py

@@ -2,8 +2,8 @@
 import pandas as pd
 import matplotlib.pyplot as plt 
 import matplotlib.patches as patches
-from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
-from mpl_toolkits.axes_grid1.inset_locator import mark_inset
+# from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
+# from mpl_toolkits.axes_grid1.inset_locator import mark_inset
 import os
 import numpy as np
 
@@ -20,7 +20,7 @@
 N = 50
 one_N = speedac[speedac["N"] == N].copy()
 
-fig, ax = plt.subplots(1, 2)
+fig, ax = plt.subplots(1, 3)
 
 plot_settings = {
                 "linestyle" : "-",
@@ -41,21 +41,37 @@
                  label="A = {0}".format(int(i)),
                  **plot_settings)
 
-ax[0].set_xlabel("Ratio of slow/fast reactions")
+ax[0].set_xlabel("Ratio of slow/fast reaction rates")
 ax[0].set_ylabel("Accuracy")
 #ax[0].legend(loc="lower center")
-ax[0].text(-0.3, 1.1, "a", transform=ax[0].transAxes, fontsize=10)
 
-ax[1].set_xlabel("Ratio of slow/fast reactions")
+ax[1].set_xlabel("Ratio of slow/fast reaction rates")
 ax[1].set_ylabel("Expected halt time")
 leg = ax[1].legend()
 leg, ax[1] = shift_legend(ax[1], leg, yshift=0.1)
-ax[1].text(-0.35, 1.05, "b", transform=ax[1].transAxes, fontsize=10)
 
-fig.set_size_inches(cm2inch(7.9, 3.5))
+#####################
+### Accuracy decrease with moleucles 
+#############
+acc_down = pd.read_csv("paper/maximum_out_S4_R3/Bimol_1_tf10000.tsv", sep="\t", names=["N", "opt_score", "one_score"])
+ax[2].plot(acc_down["N"], acc_down["opt_score"],**plot_settings)
+ax[2].set_xscale('log')
+ax[2].set_ylim(0, 1.1)
+#cycler = matplotlib.rcParams['axes.color_cycle']
+ax[2].axvline(100, color="gray", linewidth=0.5)
+ax[2].set_xlabel("Total molecules ($n$)")
+ax[2].set_ylabel("Accuracy")
+
+ly = 0.92
+ax[0].text(0.01, ly, "a", transform=fig.transFigure, fontsize=10)
+ax[1].text(0.35,  ly, "b", transform=fig.transFigure, fontsize=10)
+ax[1].text(0.69,  ly, "c", transform=fig.transFigure, fontsize=10)
+
+
+fig.set_size_inches(cm2inch(12, 3.5))
 
 #fig.tight_layout()
-fig.subplots_adjust(left= 0.15,  # the left side of the subplots of the figure
+fig.subplots_adjust(left= 0.10,  # the left side of the subplots of the figure
                    right = 0.99,   # the right side of the subplots of the figure
                    bottom = 0.3,   # the bottom of the subplots of the figure
                    top = 0.85,      # the top of the subplots of the figure

paper/maximum_out_S4_R3/Bimol_1_tf10000.tsv

@@ -0,0 +1,21 @@
+1.000000	1.000000	0.363000
+2.000000	0.998000	0.074000
+3.000000	0.998000	0.015000
+5.000000	0.997000	0.004000
+7.000000	0.996000	0.000000
+10.000000	0.995000	0.000000
+20.000000	0.980000	0.000000
+30.000000	0.965000	0.000000
+50.000000	0.961000	0.000000
+70.000000	0.931000	0.000000
+100.000000	0.906000	0.000000
+200.000000	0.832000	0.000000
+300.000000	0.768000	0.000000
+500.000000	0.604000	0.000000
+700.000000	0.542000	0.000000
+1000.000000	0.398000	0.000000
+2000.000000	0.150000	0.000000
+3000.000000	0.055000	0.000000
+5000.000000	0.010000	0.000000
+7000.000000	0.001000	0.000000
+10000.000000	0.000000	0.000000