def plot_all_scan(scan_res, selections, plot_selections, unit_dict,
param_val_fun, param_desc):
plot_all = get_plot_all_fun(selections, plot_selections, unit_dict)
lets = [x for x in "efcdab"]
fig, big_ax = plt.subplots()
aux.clean_big_ax(big_ax)
inset_dict = aux.get_inset_loc(nx=2, ny=3, hs=0.1, vs=0.05)
axes = [big_ax.inset_axes(inset_dict[key]) for key in inset_dict]
big_ax.set_xlabel("time [min]")
plot_all(scan_res, 80, axes)
for ax, let in zip(axes, lets):
if let in "bdf":
ax.text(-0.17,
1.02,
"({})".format(let),
transform=ax.transAxes,
fontsize=12)
if let in "ace":
ax.text(-0.25,
1.02,
"({})".format(let),
transform=ax.transAxes,
fontsize=12)
cb_ax, kw = mpl.colorbar.make_axes(big_ax,
orientation="vertical",
fraction=0.15,
aspect=40,
pad=0.02)
param_vals = param_val_fun(scan_res)
cmap = plt.cm.coolwarm
cb = aux.make_cb(cb_ax, list(param_vals), cmap, "vertical")
cb.set_label(param_desc)
cb.ax.set_yticklabels(param_vals)
def plot_all_scan(scan_res_double, plot_selections, unit_dict, param_val_fun, param_desc):
plot_all = get_plot_all_fun(unit_dict)
lets = [x for x in "cba"]
fig, big_ax = plt.subplots()
aux.clean_big_ax(big_ax)
inset_dict = aux.get_inset_loc(nx=2, ny=3, hs=0.02, vs=0.05)
st_axes = [big_ax.inset_axes(inset_dict[key]) for key in inset_dict if key[0] == "0"]
sf_axes = [big_ax.inset_axes(inset_dict[key]) for key in inset_dict if key[0] == "1"]
axes_double = [st_axes, sf_axes]
big_ax.set_xlabel("time [min]")
plot_all(scan_res_double, plot_selections, 80, axes_double)
st_axes[2].set_title("stress sensing")
sf_axes[2].set_title("plain")
for ax in sf_axes:
ax.set_ylabel(None)
ax.set_yticklabels([])
for ax, let in zip(st_axes, lets):
ax.text(-0.25, 1.02, "({})".format(let), transform=ax.transAxes, fontsize=12)
for ax_st, ax_sf in zip(st_axes, sf_axes):
y_lim = max(ax_st.get_ylim()[1], ax_sf.get_ylim()[1])
ax_st.set_ylim(top=y_lim)
ax_sf.set_ylim(top=y_lim)
for ax in [ax_st, ax_sf]:
aux.make_grid(ax)
cb_ax, kw = mpl.colorbar.make_axes(big_ax, orientation="vertical", fraction=0.15, aspect=40, pad=0.02)
param_vals = param_val_fun(scan_res_double[0])
cmap = plt.cm.coolwarm
cb = aux.make_cb(cb_ax, list(param_vals), cmap, "vertical")
cb.set_label(param_desc)
cb.ax.set_yticklabels(param_vals)
def plot_tv(result_df: pd.DataFrame, param_desc, vol_range, param_val_fun):
fig, ax = plt.subplots(1, 1, figsize=(6, 4))
aux.clean_big_ax(ax)
gs = aux.loc(nrows=1, ncols=2, hs=0.1, vs=0, width_ratios=(1 / 2, 1 / 2))
tax, vax = [ax.inset_axes(gs[0, i]) for i in range(gs.shape[1])]
pvb.plot_vdiv_y_multi(result_df, "v_trans", vax)
pvb.plot_vdiv_y_multi(result_df, "t_g1", tax)
pad = 0.05 * (vol_range[-1] - vol_range[0])
vax.set_xlim(vol_range[0] - pad, vol_range[-1] + pad)
cb_ax, kw = mpl.colorbar.make_axes(ax, fraction=0.15, aspect=25, pad=0.02)
param_vals = param_val_fun(scan_results)
cb = aux.make_cb(ax=cb_ax,
values=param_vals,
cmap=mpl.cm.coolwarm,
orientation="vertical")
cb.ax.set_yticklabels(param_vals)
cb.set_label(param_desc)
def plot_all(scan_res, selections, plot_selections, unit_dict, tt=100):
plot_all = get_plot_all_fun(selections, plot_selections, unit_dict)
fig, big_ax = plt.subplots(figsize=(7, 7))
aux.clean_big_ax(big_ax)
inset_dict = aux.get_inset_loc(nx=2, ny=3, hs=0.1, vs=0.05)
axes = [big_ax.inset_axes(inset_dict[key]) for key in inset_dict]
big_ax.set_xlabel("time [min]")
plot_all(scan_res, tt, axes)
cb_ax, kw = mpl.colorbar.make_axes(big_ax,
orientation="vertical",
fraction=0.15,
aspect=40,
pad=0.02)
param_vals = [round(sr[0], 2) for sr in scan_res]
cmap = plt.cm.coolwarm
cb = aux.make_cb(cb_ax, list(param_vals), cmap, "vertical")
cb.set_label("volume after division [fL]")
cb.ax.set_yticklabels(param_vals)
def plot_all_scan(scan_res, plot_selections, unit_dict, param_val_fun,
param_desc):
fig, big_ax = plt.subplots()
aux.clean_big_ax(big_ax)
inset_dict = aux.get_inset_loc(nx=2, ny=1, hs=0.08, vs=0.05)
axes = [big_ax.inset_axes(inset_dict[key]) for key in inset_dict]
big_ax.set_xlabel("time [min]")
plot_whi3p_stress(axes, plot_selections, unit_dict, scan_res, 80)
axes[0].set_ylabel(unit_dict[plot_selections[0]])
# if let in "bdf":
# ax.text(-0.17, 1.02, "({})".format(let), transform = ax.transAxes, fontsize=12)
# if let in "ace":
# ax.text(-0.25, 1.02, "({})".format(let), transform = ax.transAxes, fontsize=12)
for ax in axes:
aux.make_grid(ax)
cb_ax, kw = mpl.colorbar.make_axes(big_ax,
orientation="vertical",
fraction=0.15,
aspect=40,
pad=0.02)
param_vals = param_val_fun(scan_res)
cmap = plt.cm.coolwarm
cb = aux.make_cb(cb_ax, list(param_vals), cmap, "vertical")
cb.set_label(param_desc)
cb.ax.set_yticklabels(param_vals)
axes[1].text(-0.15,
1.02,
"({})".format("b"),
transform=axes[1].transAxes,
fontsize=12)
axes[0].text(-0.25,
1.02,
"({})".format("a"),
transform=axes[0].transAxes,
fontsize=12)
pad=0.06) for ax in fig.axes
]
cb_axes = [cb[0] for cb in cbs]
### kg scan
kgs = aux.get_rates_from_p_scan(scans[2])
kpCln3 = [scan[0] for scan in scans[1]]
kpCln12 = ["off", "on"]
vals = [kpCln12, kpCln3, kgs]
cmaps = [
mpl.colors.LinearSegmentedColormap.from_list("", list(color_t))
for color_t in colors
]
colorbars = [
aux.make_cb(cb_ax, val, cmap, "horizontal")
for cb_ax, val, cmap in zip(cb_axes, vals, cmaps)
]
labels = [
"Cln12 positive feedback", "Cln3 prod. rate [a.u./s]",
"G1 growth rate [fL/min]"
]
for cb, label, val in zip(colorbars, labels, vals):
cb.set_label(label)
cb.ax.set_xticklabels(val)
cb.ax.xaxis.set_label_position('top')
lets = "abc"
xs = [-0.06, -0.06, -0.06]
for ax, let, x in zip(whi5_axes, lets, xs):
ax.set_xticklabels([])