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import matplotlib.pyplot as plt |
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import numpy as np |
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import datetime as dt |
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import matplotlib as mpl |
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from metpy.cbook import get_test_data |
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from metpy.calc import dewpoint_rh |
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from metpy.units import units |
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def calc_mslp(t, p, h): |
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return p * ( 1 - (0.0065 * h) / (t + 0.0065 * h + 273.15)) ** (-5.257) |
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# Make meteogram plot |
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class Meteogram(object): |
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""" Plot a time series of meteorological data from a particular station as a meteogram with standard variables |
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to visualize, including thermodynamic, kinematic, and pressure. The functions below control the plotting |
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of each variable. |
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TO DO: Make the subplot creation dynamic so the number of rows is not static as it is currently. """ |
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def __init__(self, fig, dates, probeid, time=dt.datetime.utcnow() ,axis=0): |
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""" |
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Required input: |
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fig: figure object |
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dates: array of dates corresponding to the data |
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probeid: ID of the station |
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Optional Input: |
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time: Time the data is to be plotted |
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axis: number that controls the new axis to be plotted (FOR FUTURE) |
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""" |
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self.start = dates[0] |
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self.fig = fig |
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self.end = dates[-1] |
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self.axis_num = 0 |
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self.dates = mpl.dates.date2num(dates) |
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self.time = time.strftime("%Y-%m-%d %H:%M UTC") |
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self.title = 'Latest Ob Time: {0}\nProbe ID: {1}'.format(self.time, probeid) |
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def plot_winds(self, ws, wd, wsmax, plot_range=[0,20,1]): |
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""" |
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Required input: |
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ws: Wind speeds (knots) |
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wd: Wind direction (degrees) |
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wsmax: Wind gust (knots) |
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Optional Input: |
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plot_range: Data range for making figure |
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""" |
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# PLOT WIND SPEED AND WIND DIRECTION |
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self.ax1 = fig.add_subplot(4, 1, 1) |
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ln1 = self.ax1.plot(self.dates, |
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ws, |
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label='Wind Speed' |
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) |
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plt.fill_between(self.dates, ws, 0) |
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self.ax1.set_xlim(self.start, self.end) |
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#self.ax1.get_xaxis().set_ticks([(self.starttime+dt.timedelta(hours=i*4)) for i in np.arange(0,7)]) |
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plt.ylabel('Wind Speed (knots)', multialignment='center') |
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plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5) |
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ln2 = self.ax1.plot(self.dates, |
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wsmax, |
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'.r', |
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label='3-sec Wind Speed Max') |
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plt.setp(self.ax1.get_xticklabels(), visible=True) |
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ax7 = self.ax1.twinx() |
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ln3 = ax7.plot(self.dates, |
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wd, |
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'.k', linewidth=0.5, label='Wind Direction') |
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plt.ylabel('Wind\nDirection\n(degrees)', multialignment='center') |
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plt.ylim(0, 360) |
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plt.yticks(np.arange(45,405,90),['NE','SE','SW','NW']) |
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lns = ln1+ln2+ln3 |
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labs = [l.get_label() for l in lns] |
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plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC')) |
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ax7.legend(lns, labs, loc='upper center', bbox_to_anchor=(0.5,1.2), ncol=3, prop={'size':12}) |
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def plot_thermo(self, t, td, plot_range=[10,90,2]): |
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""" |
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Required input: |
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T: Temperature (deg F) |
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TD: Dewpoint (deg F) |
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Optional Input: |
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plot_range: Data range for making figure |
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""" |
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# PLOT TEMPERATURE AND DEWPOINT |
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self.ax2 = fig.add_subplot(4, 1, 2, sharex=self.ax1) |
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ln4 = self.ax2.plot(self.dates, |
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t, |
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'r-', |
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label='Temperature') |
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plt.fill_between(self.dates, |
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t, |
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td, |
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color='r') |
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plt.setp(self.ax2.get_xticklabels(), visible=True) |
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plt.ylabel('Temperature\n(F)', multialignment='center') |
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plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5) |
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self.ax2.set_ylim(plot_range[0], plot_range[1], plot_range[2]) |
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ln5 = self.ax2.plot(self.dates, |
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td, |
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'g-', |
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label='Dewpoint') |
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plt.fill_between(self.dates, |
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td, |
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plt.ylim()[0], |
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color='g') |
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ax_twin = self.ax2.twinx() |
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# ax_twin.set_ylim(20,90,2) |
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ax_twin.set_ylim(plot_range[0], plot_range[1], plot_range[2]) |
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lns = ln4+ln5 |
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labs = [l.get_label() for l in lns] |
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plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC')) |
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self.ax2.legend(lns, labs, loc='upper center', bbox_to_anchor=(0.5,1.2), ncol=2, prop={'size':12}) |
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View Code Duplication |
def plot_rh(self, rh, plot_range=[0,100,4]): |
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""" |
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Required input: |
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RH: Relative humidity (%) |
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Optional Input: |
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plot_range: Data range for making figure |
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""" |
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# PLOT RELATIVE HUMIDITY |
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self.ax3 = fig.add_subplot(4, 1, 3, sharex=self.ax1) |
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self.ax3.plot(self.dates, |
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rh, |
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'g-', |
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label='Relative Humidity') |
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self.ax3.legend(loc='upper center', bbox_to_anchor=(0.5,1.22), prop={'size':12}) |
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plt.setp(self.ax3.get_xticklabels(), visible=True) |
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plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5) |
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self.ax3.set_ylim(plot_range[0], plot_range[1], plot_range[2]) |
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plt.fill_between(self.dates, rh, plt.ylim()[0], color='g') |
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plt.ylabel('Relative Humidity\n(%)', multialignment='center') |
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plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC')) |
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axtwin = self.ax3.twinx() |
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axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2]) |
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View Code Duplication |
def plot_pressure(self, p, plot_range=[970,1030,2]): |
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""" |
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Required input: |
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P: Mean Sea Level Pressure (hPa) |
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Optional Input: |
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plot_range: Data range for making figure |
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""" |
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# PLOT PRESSURE |
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self.ax4 = fig.add_subplot(4, 1, 4, sharex=self.ax1) |
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self.ax4.plot(self.dates, |
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p, |
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'm', |
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label='Mean Sea Level Pressure') |
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plt.ylabel('Mean Sea\nLevel Pressure\n(mb)', multialignment='center') |
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plt.ylim(plot_range[0], plot_range[1], plot_range[2]) |
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axtwin = self.ax4.twinx() |
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axtwin.set_ylim(plot_range[0], plot_range[1], plot_range[2]) |
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plt.fill_between(self.dates, p, plt.ylim()[0], color='m') |
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plt.gca().xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H UTC')) |
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self.ax4.legend(loc='upper center', bbox_to_anchor=(0.5,1.2), prop={'size':12}) |
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plt.grid(b=True, which='major', axis='y', color='k', linestyle='--', linewidth=0.5) |
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plt.setp(self.ax4.get_xticklabels(), visible=True) |
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# OTHER OPTIONAL AXES TO PLOT |
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# plot_irradiance |
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# plot_precipitation |
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# set the starttime and endtime for plotting, 24 hour range |
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endtime = dt.datetime(2016,3,31,22,0,0,0) |
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starttime = endtime - dt.timedelta(hours=24) |
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# Height of the station to calculate MSLP |
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hgt_example = 292. |
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# Parse dates from .csv file, knowing their format as a string and convert to datetime |
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def parse_date(date): |
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return dt.datetime.strptime(date,"%Y-%m-%d %H:%M:%S") |
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testdata = np.genfromtxt(get_test_data('timeseries.csv', False), names=True, dtype=None, |
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usecols=list(range(1,8)), |
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converters={'DATE': parse_date}, delimiter=',') |
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# Temporary variables for ease |
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temp = testdata['T'] |
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pres = testdata['P'] |
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rh = testdata['RH'] |
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ws = testdata['WS'] |
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wsmax = testdata['WSMAX'] |
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wd = testdata['WD'] |
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date = testdata['DATE'] |
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# ID For Plotting on Meteogram |
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probe_id = '0102A' |
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data = dict() |
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data['wind_speed'] = (np.array(ws) * units('m/s')).to(units('knots')) |
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data['wind_speed_max'] = (np.array(wsmax) * units('m/s')).to(units('knots')) |
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data['wind_direction'] = np.array(wd) * units('degrees') |
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data['dewpoint'] = dewpoint_rh((np.array(temp) * units('degC')).to(units('K')),np.array(rh)/100.).to(units('degF')) |
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data['air_temperature'] = (np.array(temp) * units('degC')).to(units('degF')) |
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data['mean_slp'] = calc_mslp(np.array(temp), np.array(pres), hgt_example) * units('hPa') |
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data['relative_humidity'] = np.array(rh) |
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data['times'] = np.array(date) |
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fig = plt.figure(figsize=(20, 16)) |
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meteogram = Meteogram(fig, data['times'], probe_id) |
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meteogram.plot_winds(data['wind_speed'], data['wind_direction'], data['wind_speed_max']) |
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meteogram.plot_thermo(data['air_temperature'], data['dewpoint']) |
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meteogram.plot_rh(data['relative_humidity']) |
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meteogram.plot_pressure(data['mean_slp']) |
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fig.subplots_adjust(hspace=0.5) |
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plt.show() |
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# plt.text(1,1.02,meteogram.title,horizontalalignment='right',verticalalignment='bottom') |
Unidata /
MetPy
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