Meteogram.plot_rh() - Code Metrics - Inspection of "added an example to plot a meteogram" - Unidata/MetPy - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Pull Request — master (#318)

unknown

created 2017-02-15 17:26 UTC

Meteogram.plot_rh() A

↳ Parent: Meteogram

Complexity

Conditions

Size

Total Lines

Duplication

Lines	21
Ratio	95.45 %

Importance

Changes	4
Bugs	0	Features	0

Metric	Value
cc	1
c	4
b	0
f	0
dl	21
loc	22
rs	9.2

# Copyright (c) 2008-2016 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.pyplot as plt
import matplotlib as mpl
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=dt.datetime.utcnow(), 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)
        """
        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=[0, 20, 1]):
        """
        Required input:
            ws: Wind speeds (knots)
            wd: Wind direction (degrees)
            wsmax: Wind gust (knots)
        Optional Input:
            plot_range: Data range for making figure
        """
        # 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)
        plt.ylabel('Wind Speed (knots)', multialignment='center')
        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=[10, 90, 2]):
        """
        Required input:
            T: Temperature (deg F)
            TD: Dewpoint (deg F)
        Optional Input:
            plot_range: Data range for making figure
        """
        # PLOT TEMPERATURE AND DEWPOINT
        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=[0, 100, 4]):
        """
        Required input:
            RH: Relative humidity (%)
        Optional Input:
            plot_range: Data range for making figure
        """
        # PLOT RELATIVE HUMIDITY
        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=[970, 1030, 2]):
        """
        Required input:
            P: Mean Sea Level Pressure (hPa)
        Optional Input:
            plot_range: Data range for making figure
        """
        # PLOT PRESSURE
        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, '%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 = dict()
data['wind_speed'] = (np.array(ws) * units('m/s')).to(units('knots'))
data['wind_speed_max'] = (np.array(wsmax) * units('m/s')).to(units('knots'))
data['wind_direction'] = np.array(wd) * units('degrees')
data['dewpoint'] = dewpoint_rh((np.array(temp) * units('degC')).to(units('K')),
                               np.array(rh) / 100.).to(units('degF'))
data['air_temperature'] = (np.array(temp) * units('degC')).to(units('degF'))
data['mean_slp'] = calc_mslp(np.array(temp), np.array(pres), hgt_example) * units('hPa')
data['relative_humidity'] = np.array(rh)
data['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) 2008-2016 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		import matplotlib.pyplot as plt
13		import matplotlib as mpl
14		import numpy as np
15		from metpy.calc import dewpoint_rh
16		from metpy.cbook import get_test_data
17		from metpy.units import units
18
19
20		def calc_mslp(t, p, h):
21		return p * (1 - (0.0065 * h) / (t + 0.0065 * h + 273.15)) ** (-5.257)
22
23
24		# Make meteogram plot
25		class Meteogram(object):
26		""" Plot a time series of meteorological data from a particular station as a
27		meteogram with standard variables to visualize, including thermodynamic,
28		kinematic, and pressure. The functions below control the plotting of each
29		variable.
30		TO DO: Make the subplot creation dynamic so the number of rows is not
31		static as it is currently. """
32
33		def __init__(self, fig, dates, probeid, time=dt.datetime.utcnow(), axis=0):
34		"""
35		Required input:
36		fig: figure object
37		dates: array of dates corresponding to the data
38		probeid: ID of the station
39		Optional Input:
40		time: Time the data is to be plotted
41		axis: number that controls the new axis to be plotted (FOR FUTURE)
42		"""
43		self.start = dates[0]
44		self.fig = fig
45		self.end = dates[-1]
46		self.axis_num = 0
47		self.dates = mpl.dates.date2num(dates)
48		self.time = time.strftime('%Y-%m-%d %H:%M UTC')
49		self.title = 'Latest Ob Time: {0}\nProbe ID: {1}'.format(self.time, probeid)
50
51		def plot_winds(self, ws, wd, wsmax, plot_range=[0, 20, 1]):
52		"""
53		Required input:
54		ws: Wind speeds (knots)
55		wd: Wind direction (degrees)
56		wsmax: Wind gust (knots)
57		Optional Input:
58		plot_range: Data range for making figure
59		"""
60		# PLOT WIND SPEED AND WIND DIRECTION
61		self.ax1 = fig.add_subplot(4, 1, 1)
62		ln1 = self.ax1.plot(self.dates, ws, label='Wind Speed')
63		plt.fill_between(self.dates, ws, 0)
64		self.ax1.set_xlim(self.start, self.end)
65		plt.ylabel('Wind Speed (knots)', multialignment='center')
66		plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
67		ln2 = self.ax1.plot(self.dates,
68		wsmax,
69		'.r',
70		label='3-sec Wind Speed Max')
71		plt.setp(self.ax1.get_xticklabels(), visible=True)
72		ax7 = self.ax1.twinx()
73		ln3 = ax7.plot(self.dates,
74		wd,
75		'.k',
76		linewidth=0.5,
77		label='Wind Direction')
78		plt.ylabel('Wind\nDirection\n(degrees)', multialignment='center')
79		plt.ylim(0, 360)
80		plt.yticks(np.arange(45, 405, 90), ['NE', 'SE', 'SW', 'NW'])
81		lns = ln1 + ln2 + ln3
82		labs = [l.get_label() for l in lns]
83		plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
84		ax7.legend(lns, labs, loc='upper center',
85		bbox_to_anchor=(0.5, 1.2), ncol=3, prop={'size': 12})
86
87		def plot_thermo(self, t, td, plot_range=[10, 90, 2]):
88		"""
89		Required input:
90		T: Temperature (deg F)
91		TD: Dewpoint (deg F)
92		Optional Input:
93		plot_range: Data range for making figure
94		"""
95		# PLOT TEMPERATURE AND DEWPOINT
96		self.ax2 = fig.add_subplot(4, 1, 2, sharex=self.ax1)
97		ln4 = self.ax2.plot(self.dates,
98		t,
99		'r-',
100		label='Temperature')
101		plt.fill_between(self.dates,
102		t,
103		td,
104		color='r')
105		plt.setp(self.ax2.get_xticklabels(), visible=True)
106		plt.ylabel('Temperature\n(F)', multialignment='center')
107		plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
108		self.ax2.set_ylim(plot_range[0], plot_range[1], plot_range[2])
109		ln5 = self.ax2.plot(self.dates,
110		td,
111		'g-',
112		label='Dewpoint')
113		plt.fill_between(self.dates,
114		td,
115		plt.ylim()[0],
116	View Code Duplication	color='g')
		0 ignored issues – show Duplication introduced 2017-02-14 21:18 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
117		ax_twin = self.ax2.twinx()
118		# ax_twin.set_ylim(20,90,2)
119		ax_twin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
120		lns = ln4 + ln5
121		labs = [l.get_label() for l in lns]
122		plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
123
124		self.ax2.legend(lns, labs, loc='upper center',
125		bbox_to_anchor=(0.5, 1.2), ncol=2, prop={'size': 12})
126
127		def plot_rh(self, rh, plot_range=[0, 100, 4]):
128		"""
129		Required input:
130		RH: Relative humidity (%)
131		Optional Input:
132		plot_range: Data range for making figure
133		"""
134		# PLOT RELATIVE HUMIDITY
135		self.ax3 = fig.add_subplot(4, 1, 3, sharex=self.ax1)
136		self.ax3.plot(self.dates,
137		rh,
138		'g-',
139	View Code Duplication	label='Relative Humidity')
		0 ignored issues – show Duplication introduced 2017-02-14 21:18 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
140		self.ax3.legend(loc='upper center', bbox_to_anchor=(0.5, 1.22), prop={'size': 12})
141		plt.setp(self.ax3.get_xticklabels(), visible=True)
142		plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
143		self.ax3.set_ylim(plot_range[0], plot_range[1], plot_range[2])
144		plt.fill_between(self.dates, rh, plt.ylim()[0], color='g')
145		plt.ylabel('Relative Humidity\n(%)', multialignment='center')
146		plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
147		axtwin = self.ax3.twinx()
148		axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
149
150		def plot_pressure(self, p, plot_range=[970, 1030, 2]):
151		"""
152		Required input:
153		P: Mean Sea Level Pressure (hPa)
154		Optional Input:
155		plot_range: Data range for making figure
156		"""
157		# PLOT PRESSURE
158		self.ax4 = fig.add_subplot(4, 1, 4, sharex=self.ax1)
159		self.ax4.plot(self.dates,
160		p,
161		'm',
162		label='Mean Sea Level Pressure')
163		plt.ylabel('Mean Sea\nLevel Pressure\n(mb)', multialignment='center')
164		plt.ylim(plot_range[0], plot_range[1], plot_range[2])
165		axtwin = self.ax4.twinx()
166		axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2])
167		plt.fill_between(self.dates, p, plt.ylim()[0], color='m')
168		plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC'))
169		self.ax4.legend(loc='upper center', bbox_to_anchor=(0.5, 1.2), prop={'size': 12})
170		plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5)
171		plt.setp(self.ax4.get_xticklabels(), visible=True)
172		# OTHER OPTIONAL AXES TO PLOT
173		# plot_irradiance
174		# plot_precipitation
175
176
177		# set the starttime and endtime for plotting, 24 hour range
178		endtime = dt.datetime(2016, 3, 31, 22, 0, 0, 0)
179		starttime = endtime - dt.timedelta(hours=24)
180
181		# Height of the station to calculate MSLP
182		hgt_example = 292.
183
184
185		# Parse dates from .csv file, knowing their format as a string and convert to datetime
186		def parse_date(date):
187		return dt.datetime.strptime(date, '%Y-%m-%d %H:%M:%S')
188
189
190		testdata = np.genfromtxt(get_test_data('timeseries.csv', False), names=True, dtype=None,
191		usecols=list(range(1, 8)),
192		converters={'DATE': parse_date}, delimiter=',')
193
194		# Temporary variables for ease
195		temp = testdata['T']
196		pres = testdata['P']
197		rh = testdata['RH']
198		ws = testdata['WS']
199		wsmax = testdata['WSMAX']
200		wd = testdata['WD']
201		date = testdata['DATE']
202
203		# ID For Plotting on Meteogram
204		probe_id = '0102A'
205
206		data = dict()
207		data['wind_speed'] = (np.array(ws) * units('m/s')).to(units('knots'))
208		data['wind_speed_max'] = (np.array(wsmax) * units('m/s')).to(units('knots'))
209		data['wind_direction'] = np.array(wd) * units('degrees')
210		data['dewpoint'] = dewpoint_rh((np.array(temp) * units('degC')).to(units('K')),
211		np.array(rh) / 100.).to(units('degF'))
212		data['air_temperature'] = (np.array(temp) * units('degC')).to(units('degF'))
213		data['mean_slp'] = calc_mslp(np.array(temp), np.array(pres), hgt_example) * units('hPa')
214		data['relative_humidity'] = np.array(rh)
215		data['times'] = np.array(date)
216
217		fig = plt.figure(figsize=(20, 16))
218		meteogram = Meteogram(fig, data['times'], probe_id)
219		meteogram.plot_winds(data['wind_speed'], data['wind_direction'], data['wind_speed_max'])
220		meteogram.plot_thermo(data['air_temperature'], data['dewpoint'])
221		meteogram.plot_rh(data['relative_humidity'])
222		meteogram.plot_pressure(data['mean_slp'])
223		fig.subplots_adjust(hspace=0.5)
224		plt.show()
225

Unidata / MetPy

Pull Request — master (#318)

Meteogram.plot_rh() A

Complexity

Size

Duplication

Importance

Duplication Side-by-Side

Filter issues like