PySDM_examples.Pyrcel.profile_plotter

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 1import numpy as np
 2from matplotlib import pyplot
 3from open_atmos_jupyter_utils import show_plot
 4
 5from PySDM.physics.constants import si
 6
 7
 8class ProfilePlotter:
 9    def __init__(self, settings, legend=True, log_base=10):
10        self.settings = settings
11        self.format = "pdf"
12        self.legend = legend
13        self.log_base = log_base
14        self.ax = pyplot
15        self.fig = pyplot
16
17    def show(self):
18        pyplot.tight_layout()
19        show_plot()
20
21    def save(self, file):
22        # self.finish()
23        pyplot.savefig(file, format=self.format)
24
25    def plot(self, output):
26        self.plot_data(self.settings, output)
27
28    def plot_data(self, settings, output):
29        _, axs = pyplot.subplots(1, 2, sharey=True, figsize=(10, 5))
30        axS = axs[0]
31        if output["products"].get("S_max"):
32            SS_percent = (np.asarray(output["products"]["S_max"]) - 1) * 100
33        else:
34            SS_percent = np.asarray(output["products"]["S_max_percent"]) - 100
35        axS.plot(
36            SS_percent,
37            output["products"]["z"],
38            color="black",
39        )
40        axS.set_ylabel("Displacement [m]")
41        axS.set_xlabel("Supersaturation [%]")
42        axS.set_xlim(0, 0.7)
43        axS.set_ylim(0, 250)
44        axS.text(0.3, 52, f"max SS = {np.nanmax(SS_percent):.2f}%")
45        axS.grid()
46
47        axT = axS.twiny()
48        axT.xaxis.label.set_color("red")
49        axT.tick_params(axis="x", colors="red")
50        axT.plot(output["products"]["T"], output["products"]["z"], color="red")
51        rng = (272, 274)
52        axT.set_xlim(*rng)
53        axT.set_xticks(np.linspace(*rng, num=5))
54        axT.set_xlabel("Temperature [K]")
55
56        axR = axs[1]
57        axR.set_xscale("log")
58        axR.set_xlim(1e-2, 1e2)
59        for drop_id, volume in enumerate(output["attributes"]["volume"]):
60            axR.plot(
61                settings.formulae.trivia.radius(volume=np.asarray(volume)) / si.um,
62                output["products"]["z"],
63                color="magenta" if drop_id < settings.n_sd_per_mode[0] else "blue",
64                label=(
65                    "mode 1"
66                    if drop_id == 0
67                    else "mode 2" if drop_id == settings.n_sd_per_mode[0] else ""
68                ),
69            )
70        axR.legend(loc="upper right")
71        axR.set_xlabel("Droplet radius [μm]")

class ProfilePlotter: View Source

 9class ProfilePlotter:
10    def __init__(self, settings, legend=True, log_base=10):
11        self.settings = settings
12        self.format = "pdf"
13        self.legend = legend
14        self.log_base = log_base
15        self.ax = pyplot
16        self.fig = pyplot
17
18    def show(self):
19        pyplot.tight_layout()
20        show_plot()
21
22    def save(self, file):
23        # self.finish()
24        pyplot.savefig(file, format=self.format)
25
26    def plot(self, output):
27        self.plot_data(self.settings, output)
28
29    def plot_data(self, settings, output):
30        _, axs = pyplot.subplots(1, 2, sharey=True, figsize=(10, 5))
31        axS = axs[0]
32        if output["products"].get("S_max"):
33            SS_percent = (np.asarray(output["products"]["S_max"]) - 1) * 100
34        else:
35            SS_percent = np.asarray(output["products"]["S_max_percent"]) - 100
36        axS.plot(
37            SS_percent,
38            output["products"]["z"],
39            color="black",
40        )
41        axS.set_ylabel("Displacement [m]")
42        axS.set_xlabel("Supersaturation [%]")
43        axS.set_xlim(0, 0.7)
44        axS.set_ylim(0, 250)
45        axS.text(0.3, 52, f"max SS = {np.nanmax(SS_percent):.2f}%")
46        axS.grid()
47
48        axT = axS.twiny()
49        axT.xaxis.label.set_color("red")
50        axT.tick_params(axis="x", colors="red")
51        axT.plot(output["products"]["T"], output["products"]["z"], color="red")
52        rng = (272, 274)
53        axT.set_xlim(*rng)
54        axT.set_xticks(np.linspace(*rng, num=5))
55        axT.set_xlabel("Temperature [K]")
56
57        axR = axs[1]
58        axR.set_xscale("log")
59        axR.set_xlim(1e-2, 1e2)
60        for drop_id, volume in enumerate(output["attributes"]["volume"]):
61            axR.plot(
62                settings.formulae.trivia.radius(volume=np.asarray(volume)) / si.um,
63                output["products"]["z"],
64                color="magenta" if drop_id < settings.n_sd_per_mode[0] else "blue",
65                label=(
66                    "mode 1"
67                    if drop_id == 0
68                    else "mode 2" if drop_id == settings.n_sd_per_mode[0] else ""
69                ),
70            )
71        axR.legend(loc="upper right")
72        axR.set_xlabel("Droplet radius [μm]")

ProfilePlotter(settings, legend=True, log_base=10) View Source

10    def __init__(self, settings, legend=True, log_base=10):
11        self.settings = settings
12        self.format = "pdf"
13        self.legend = legend
14        self.log_base = log_base
15        self.ax = pyplot
16        self.fig = pyplot

settings

format

legend

log_base

fig

def show(self): View Source

18    def show(self):
19        pyplot.tight_layout()
20        show_plot()

def save(self, file): View Source

22    def save(self, file):
23        # self.finish()
24        pyplot.savefig(file, format=self.format)

def plot(self, output): View Source

26    def plot(self, output):
27        self.plot_data(self.settings, output)

def plot_data(self, settings, output): View Source

29    def plot_data(self, settings, output):
30        _, axs = pyplot.subplots(1, 2, sharey=True, figsize=(10, 5))
31        axS = axs[0]
32        if output["products"].get("S_max"):
33            SS_percent = (np.asarray(output["products"]["S_max"]) - 1) * 100
34        else:
35            SS_percent = np.asarray(output["products"]["S_max_percent"]) - 100
36        axS.plot(
37            SS_percent,
38            output["products"]["z"],
39            color="black",
40        )
41        axS.set_ylabel("Displacement [m]")
42        axS.set_xlabel("Supersaturation [%]")
43        axS.set_xlim(0, 0.7)
44        axS.set_ylim(0, 250)
45        axS.text(0.3, 52, f"max SS = {np.nanmax(SS_percent):.2f}%")
46        axS.grid()
47
48        axT = axS.twiny()
49        axT.xaxis.label.set_color("red")
50        axT.tick_params(axis="x", colors="red")
51        axT.plot(output["products"]["T"], output["products"]["z"], color="red")
52        rng = (272, 274)
53        axT.set_xlim(*rng)
54        axT.set_xticks(np.linspace(*rng, num=5))
55        axT.set_xlabel("Temperature [K]")
56
57        axR = axs[1]
58        axR.set_xscale("log")
59        axR.set_xlim(1e-2, 1e2)
60        for drop_id, volume in enumerate(output["attributes"]["volume"]):
61            axR.plot(
62                settings.formulae.trivia.radius(volume=np.asarray(volume)) / si.um,
63                output["products"]["z"],
64                color="magenta" if drop_id < settings.n_sd_per_mode[0] else "blue",
65                label=(
66                    "mode 1"
67                    if drop_id == 0
68                    else "mode 2" if drop_id == settings.n_sd_per_mode[0] else ""
69                ),
70            )
71        axR.legend(loc="upper right")
72        axR.set_xlabel("Droplet radius [μm]")