Meteogram.plot_thermo() - Code Metrics - Unidata/MetPy - Measure and Improve Code Quality continuously with Scrutinizer

Meteogram.plot_thermo() B
last analyzed 2017-11-02 22:59 UTC

↳ Parent: Meteogram

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Ratio	0 %

Importance

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Metric	Value
cc	3
c	0
b	0
f	0
dl	0
loc	41
rs	8.8571

# Copyright (c) 2017 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Meteogram
=========

Plots time series data as a meteogram.
"""

import datetime as dt

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

from metpy.calc import dewpoint_rh
from metpy.cbook import get_test_data
from metpy.units import units


def calc_mslp(t, p, h):
    return p * (1 - (0.0065 * h) / (t + 0.0065 * h + 273.15)) ** (-5.257)


# Make meteogram plot
class Meteogram(object):
    """ Plot a time series of meteorological data from a particular station as a
    meteogram with standard variables to visualize, including thermodynamic,
    kinematic, and pressure. The functions below control the plotting of each
    variable.
    TO DO: Make the subplot creation dynamic so the number of rows is not
    static as it is currently. """

    def __init__(self, fig, dates, probeid, time=None, axis=0):
        """
        Required input:
            fig: figure object
            dates: array of dates corresponding to the data
            probeid: ID of the station
        Optional Input:
            time: Time the data is to be plotted
            axis: number that controls the new axis to be plotted (FOR FUTURE)
        """
        if not time:
            time = dt.datetime.utcnow()
        self.start = dates[0]
        self.fig = fig
        self.end = dates[-1]
        self.axis_num = 0
        self.dates = mpl.dates.date2num(dates)
        self.time = time.strftime('%Y-%m-%d %H:%M UTC')
        self.title = 'Latest Ob Time: {0}\nProbe ID: {1}'.format(self.time, probeid)

    def plot_winds(self, ws, wd, wsmax, plot_range=None):
        """
        Required input:
            ws: Wind speeds (knots)
            wd: Wind direction (degrees)
            wsmax: Wind gust (knots)
        Optional Input:
            plot_range: Data range for making figure (list of (min,max,step))
        """
        # PLOT WIND SPEED AND WIND DIRECTION
        self.ax1 = fig.add_subplot(4, 1, 1)
        ln1 = self.ax1.plot(self.dates, ws, label='Wind Speed')
        plt.fill_between(self.dates, ws, 0)
        self.ax1.set_xlim(self.start, self.end)
        if not plot_range:
            plot_range = [0, 20, 1]
        plt.ylabel('Wind Speed (knots)', multialignment='center')
        self.ax1.set_ylim(plot_range[0], plot_range[1], plot_range[2])
        plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
        ln2 = self.ax1.plot(self.dates,
                            wsmax,
                            '.r',
                            label='3-sec Wind Speed Max')
        plt.setp(self.ax1.get_xticklabels(), visible=True)
        ax7 = self.ax1.twinx()
        ln3 = ax7.plot(self.dates,
                       wd,
                       '.k',
                       linewidth=0.5,
                       label='Wind Direction')
        plt.ylabel('Wind\nDirection\n(degrees)', multialignment='center')
        plt.ylim(0, 360)
        plt.yticks(np.arange(45, 405, 90), ['NE', 'SE', 'SW', 'NW'])
        lns = ln1 + ln2 + ln3
        labs = [l.get_label() for l in lns]
        plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
        ax7.legend(lns, labs, loc='upper center',
                   bbox_to_anchor=(0.5, 1.2), ncol=3, prop={'size': 12})

    def plot_thermo(self, t, td, plot_range=None):
        """
        Required input:
            T: Temperature (deg F)
            TD: Dewpoint (deg F)
        Optional Input:
            plot_range: Data range for making figure (list of (min,max,step))
        """
        # PLOT TEMPERATURE AND DEWPOINT
        if not plot_range:
            plot_range = [10, 90, 2]
        self.ax2 = fig.add_subplot(4, 1, 2, sharex=self.ax1)
        ln4 = self.ax2.plot(self.dates,
                            t,
                            'r-',
                            label='Temperature')
        plt.fill_between(self.dates,
                         t,
                         td,
                         color='r')
        plt.setp(self.ax2.get_xticklabels(), visible=True)
        plt.ylabel('Temperature\n(F)', multialignment='center')
        plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
        self.ax2.set_ylim(plot_range[0], plot_range[1], plot_range[2])
        ln5 = self.ax2.plot(self.dates,
                            td,
                            'g-',
                            label='Dewpoint')
        plt.fill_between(self.dates,
                         td,
                         plt.ylim()[0],
                         color='g')
        ax_twin = self.ax2.twinx()
        #    ax_twin.set_ylim(20,90,2)
        ax_twin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
        lns = ln4 + ln5
        labs = [l.get_label() for l in lns]
        plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))

        self.ax2.legend(lns, labs, loc='upper center',
                        bbox_to_anchor=(0.5, 1.2), ncol=2, prop={'size': 12})

    def plot_rh(self, rh, plot_range=None):
        """
        Required input:
            RH: Relative humidity (%)
        Optional Input:
            plot_range: Data range for making figure (list of (min,max,step))
        """
        # PLOT RELATIVE HUMIDITY
        if not plot_range:
            plot_range = [0, 100, 4]
        self.ax3 = fig.add_subplot(4, 1, 3, sharex=self.ax1)
        self.ax3.plot(self.dates,
                      rh,
                      'g-',
                      label='Relative Humidity')
        self.ax3.legend(loc='upper center', bbox_to_anchor=(0.5, 1.22), prop={'size': 12})
        plt.setp(self.ax3.get_xticklabels(), visible=True)
        plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
        self.ax3.set_ylim(plot_range[0], plot_range[1], plot_range[2])
        plt.fill_between(self.dates, rh, plt.ylim()[0], color='g')
        plt.ylabel('Relative Humidity\n(%)', multialignment='center')
        plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
        axtwin = self.ax3.twinx()
        axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2])

    def plot_pressure(self, p, plot_range=None):
        """
        Required input:
            P: Mean Sea Level Pressure (hPa)
        Optional Input:
            plot_range: Data range for making figure (list of (min,max,step))
        """
        # PLOT PRESSURE
        if not plot_range:
            plot_range = [970, 1030, 2]
        self.ax4 = fig.add_subplot(4, 1, 4, sharex=self.ax1)
        self.ax4.plot(self.dates,
                      p,
                      'm',
                      label='Mean Sea Level Pressure')
        plt.ylabel('Mean Sea\nLevel Pressure\n(mb)', multialignment='center')
        plt.ylim(plot_range[0], plot_range[1], plot_range[2])
        axtwin = self.ax4.twinx()
        axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
        plt.fill_between(self.dates, p, plt.ylim()[0], color='m')
        plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
        self.ax4.legend(loc='upper center', bbox_to_anchor=(0.5, 1.2), prop={'size': 12})
        plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
        plt.setp(self.ax4.get_xticklabels(), visible=True)
        # OTHER OPTIONAL AXES TO PLOT
        # plot_irradiance
        # plot_precipitation


# set the starttime and endtime for plotting, 24 hour range
endtime = dt.datetime(2016, 3, 31, 22, 0, 0, 0)
starttime = endtime - dt.timedelta(hours=24)

# Height of the station to calculate MSLP
hgt_example = 292.


# Parse dates from .csv file, knowing their format as a string and convert to datetime
def parse_date(date):
    return dt.datetime.strptime(date.decode('ascii'), '%Y-%m-%d %H:%M:%S')


testdata = np.genfromtxt(get_test_data('timeseries.csv', False), names=True, dtype=None,
                         usecols=list(range(1, 8)),
                         converters={'DATE': parse_date}, delimiter=',')

# Temporary variables for ease
temp = testdata['T']
pres = testdata['P']
rh = testdata['RH']
ws = testdata['WS']
wsmax = testdata['WSMAX']
wd = testdata['WD']
date = testdata['DATE']

# ID For Plotting on Meteogram
probe_id = '0102A'

data = {'wind_speed': (np.array(ws) * units('m/s')).to(units('knots')),
        'wind_speed_max': (np.array(wsmax) * units('m/s')).to(units('knots')),
        'wind_direction': np.array(wd) * units('degrees'),
        'dewpoint': dewpoint_rh((np.array(temp) * units('degC')).to(units('K')),
                                np.array(rh) / 100.).to(units('degF')),
        'air_temperature': (np.array(temp) * units('degC')).to(units('degF')),
        'mean_slp': calc_mslp(np.array(temp), np.array(pres), hgt_example) * units('hPa'),
        'relative_humidity': np.array(rh), 'times': np.array(date)}

fig = plt.figure(figsize=(20, 16))
meteogram = Meteogram(fig, data['times'], probe_id)
meteogram.plot_winds(data['wind_speed'], data['wind_direction'], data['wind_speed_max'])
meteogram.plot_thermo(data['air_temperature'], data['dewpoint'])
meteogram.plot_rh(data['relative_humidity'])
meteogram.plot_pressure(data['mean_slp'])
fig.subplots_adjust(hspace=0.5)
plt.show()


1			# Copyright (c) 2017 MetPy Developers.
2			# Distributed under the terms of the BSD 3-Clause License.
3			# SPDX-License-Identifier: BSD-3-Clause
4			"""
5			Meteogram
6			=========
7
8			Plots time series data as a meteogram.
9			"""
10
11			import datetime as dt
12
13			import matplotlib as mpl
14			import matplotlib.pyplot as plt
15			import numpy as np
16
17			from metpy.calc import dewpoint_rh
18			from metpy.cbook import get_test_data
19			from metpy.units import units
20
21
22			def calc_mslp(t, p, h):
23			return p * (1 - (0.0065 * h) / (t + 0.0065 * h + 273.15)) ** (-5.257)
24
25
26			# Make meteogram plot
27			class Meteogram(object):
28			""" Plot a time series of meteorological data from a particular station as a
29			meteogram with standard variables to visualize, including thermodynamic,
30			kinematic, and pressure. The functions below control the plotting of each
31			variable.
32			TO DO: Make the subplot creation dynamic so the number of rows is not
33			static as it is currently. """
34
35			def __init__(self, fig, dates, probeid, time=None, axis=0):
36			"""
37			Required input:
38			fig: figure object
39			dates: array of dates corresponding to the data
40			probeid: ID of the station
41			Optional Input:
42			time: Time the data is to be plotted
43			axis: number that controls the new axis to be plotted (FOR FUTURE)
44			"""
45			if not time:
46			time = dt.datetime.utcnow()
47			self.start = dates[0]
48			self.fig = fig
49			self.end = dates[-1]
50			self.axis_num = 0
51			self.dates = mpl.dates.date2num(dates)
52			self.time = time.strftime('%Y-%m-%d %H:%M UTC')
53			self.title = 'Latest Ob Time: {0}\nProbe ID: {1}'.format(self.time, probeid)
54
55			def plot_winds(self, ws, wd, wsmax, plot_range=None):
56			"""
57			Required input:
58			ws: Wind speeds (knots)
59			wd: Wind direction (degrees)
60			wsmax: Wind gust (knots)
61			Optional Input:
62			plot_range: Data range for making figure (list of (min,max,step))
63			"""
64			# PLOT WIND SPEED AND WIND DIRECTION
65			self.ax1 = fig.add_subplot(4, 1, 1)
66			ln1 = self.ax1.plot(self.dates, ws, label='Wind Speed')
67			plt.fill_between(self.dates, ws, 0)
68			self.ax1.set_xlim(self.start, self.end)
69			if not plot_range:
70			plot_range = [0, 20, 1]
71			plt.ylabel('Wind Speed (knots)', multialignment='center')
72			self.ax1.set_ylim(plot_range[0], plot_range[1], plot_range[2])
73			plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
74			ln2 = self.ax1.plot(self.dates,
75			wsmax,
76			'.r',
77			label='3-sec Wind Speed Max')
78			plt.setp(self.ax1.get_xticklabels(), visible=True)
79			ax7 = self.ax1.twinx()
80			ln3 = ax7.plot(self.dates,
81			wd,
82			'.k',
83			linewidth=0.5,
84			label='Wind Direction')
85			plt.ylabel('Wind\nDirection\n(degrees)', multialignment='center')
86			plt.ylim(0, 360)
87			plt.yticks(np.arange(45, 405, 90), ['NE', 'SE', 'SW', 'NW'])
88			lns = ln1 + ln2 + ln3
89			labs = [l.get_label() for l in lns]
90			plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
91			ax7.legend(lns, labs, loc='upper center',
92			bbox_to_anchor=(0.5, 1.2), ncol=3, prop={'size': 12})
93
94			def plot_thermo(self, t, td, plot_range=None):
95			"""
96			Required input:
97			T: Temperature (deg F)
98			TD: Dewpoint (deg F)
99			Optional Input:
100			plot_range: Data range for making figure (list of (min,max,step))
101			"""
102			# PLOT TEMPERATURE AND DEWPOINT
103			if not plot_range:
104			plot_range = [10, 90, 2]
105			self.ax2 = fig.add_subplot(4, 1, 2, sharex=self.ax1)
106			ln4 = self.ax2.plot(self.dates,
107			t,
108			'r-',
109			label='Temperature')
110			plt.fill_between(self.dates,
111			t,
112			td,
113			color='r')
114			plt.setp(self.ax2.get_xticklabels(), visible=True)
115			plt.ylabel('Temperature\n(F)', multialignment='center')
116			plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
117			self.ax2.set_ylim(plot_range[0], plot_range[1], plot_range[2])
118			ln5 = self.ax2.plot(self.dates,
119			td,
120			'g-',
121			label='Dewpoint')
122			plt.fill_between(self.dates,
123			td,
124			plt.ylim()[0],
125			color='g')
126			ax_twin = self.ax2.twinx()
127			# ax_twin.set_ylim(20,90,2)
128			ax_twin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
129			lns = ln4 + ln5
130			labs = [l.get_label() for l in lns]
131			plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
132
133			self.ax2.legend(lns, labs, loc='upper center',
134			bbox_to_anchor=(0.5, 1.2), ncol=2, prop={'size': 12})
135
136			def plot_rh(self, rh, plot_range=None):
137			"""
138			Required input:
139			RH: Relative humidity (%)
140			Optional Input:
141			plot_range: Data range for making figure (list of (min,max,step))
142			"""
143			# PLOT RELATIVE HUMIDITY
144			if not plot_range:
145			plot_range = [0, 100, 4]
146			self.ax3 = fig.add_subplot(4, 1, 3, sharex=self.ax1)
147			self.ax3.plot(self.dates,
148			rh,
149			'g-',
150			label='Relative Humidity')
151			self.ax3.legend(loc='upper center', bbox_to_anchor=(0.5, 1.22), prop={'size': 12})
152			plt.setp(self.ax3.get_xticklabels(), visible=True)
153			plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
154			self.ax3.set_ylim(plot_range[0], plot_range[1], plot_range[2])
155			plt.fill_between(self.dates, rh, plt.ylim()[0], color='g')
156			plt.ylabel('Relative Humidity\n(%)', multialignment='center')
157			plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
158			axtwin = self.ax3.twinx()
159			axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
160
161			def plot_pressure(self, p, plot_range=None):
162			"""
163			Required input:
164			P: Mean Sea Level Pressure (hPa)
165			Optional Input:
166			plot_range: Data range for making figure (list of (min,max,step))
167			"""
168			# PLOT PRESSURE
169			if not plot_range:
170			plot_range = [970, 1030, 2]
171			self.ax4 = fig.add_subplot(4, 1, 4, sharex=self.ax1)
172			self.ax4.plot(self.dates,
173			p,
174			'm',
175			label='Mean Sea Level Pressure')
176			plt.ylabel('Mean Sea\nLevel Pressure\n(mb)', multialignment='center')
177			plt.ylim(plot_range[0], plot_range[1], plot_range[2])
178			axtwin = self.ax4.twinx()
179			axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
180			plt.fill_between(self.dates, p, plt.ylim()[0], color='m')
181			plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
182			self.ax4.legend(loc='upper center', bbox_to_anchor=(0.5, 1.2), prop={'size': 12})
183			plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
184			plt.setp(self.ax4.get_xticklabels(), visible=True)
185			# OTHER OPTIONAL AXES TO PLOT
186			# plot_irradiance
187			# plot_precipitation
188
189
190			# set the starttime and endtime for plotting, 24 hour range
191			endtime = dt.datetime(2016, 3, 31, 22, 0, 0, 0)
192			starttime = endtime - dt.timedelta(hours=24)
193
194			# Height of the station to calculate MSLP
195			hgt_example = 292.
196
197
198			# Parse dates from .csv file, knowing their format as a string and convert to datetime
199			def parse_date(date):
200			return dt.datetime.strptime(date.decode('ascii'), '%Y-%m-%d %H:%M:%S')
201
202
203			testdata = np.genfromtxt(get_test_data('timeseries.csv', False), names=True, dtype=None,
204			usecols=list(range(1, 8)),
205			converters={'DATE': parse_date}, delimiter=',')
206
207			# Temporary variables for ease
208			temp = testdata['T']
209			pres = testdata['P']
210			rh = testdata['RH']
211			ws = testdata['WS']
212			wsmax = testdata['WSMAX']
213			wd = testdata['WD']
214			date = testdata['DATE']
215
216			# ID For Plotting on Meteogram
217			probe_id = '0102A'
218
219			data = {'wind_speed': (np.array(ws) * units('m/s')).to(units('knots')),
220			'wind_speed_max': (np.array(wsmax) * units('m/s')).to(units('knots')),
221			'wind_direction': np.array(wd) * units('degrees'),
222			'dewpoint': dewpoint_rh((np.array(temp) * units('degC')).to(units('K')),
223			np.array(rh) / 100.).to(units('degF')),
224			'air_temperature': (np.array(temp) * units('degC')).to(units('degF')),
225			'mean_slp': calc_mslp(np.array(temp), np.array(pres), hgt_example) * units('hPa'),
226			'relative_humidity': np.array(rh), 'times': np.array(date)}
227
228			fig = plt.figure(figsize=(20, 16))
229			meteogram = Meteogram(fig, data['times'], probe_id)
230			meteogram.plot_winds(data['wind_speed'], data['wind_direction'], data['wind_speed_max'])
231			meteogram.plot_thermo(data['air_temperature'], data['dewpoint'])
232			meteogram.plot_rh(data['relative_humidity'])
233			meteogram.plot_pressure(data['mean_slp'])
234			fig.subplots_adjust(hspace=0.5)
235			plt.show()
236

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Meteogram.plot_thermo() B last analyzed 2017-11-02 22:59 UTC

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Meteogram.plot_thermo() B
last analyzed 2017-11-02 22:59 UTC