def test_windrose_mesh_size():
# Testing mesh scaling
dir_vals = [0, 0, 0, 10, 10, 10, 85, 90, 90, 90, 95, 170, 285, 288]
spd_vals = dir_vals
# Make into fake data collections
a_per = AnalysisPeriod(6, 21, 12, 6, 21, 13)
dates = [DateTime(6, 21, i) for i in range(len(dir_vals))]
spd_header = Header(Speed(), 'm/s', a_per)
dir_header = Header(GenericType('Direction', 'deg'), 'deg', a_per)
spd_data = HourlyDiscontinuousCollection(spd_header, spd_vals, dates)
dir_data = HourlyDiscontinuousCollection(dir_header, dir_vals, dates)
# Init simple dir set divided by 4
w = WindRose(dir_data, spd_data, 4)
w.legend_parameters.segment_count = 3
# Test the size of the windrose
w = WindRose(dir_data, spd_data, 4)
w.legend_parameters.segment_count = 3
w.show_zeros = False
w.show_freq = True
w.frequency_spacing_distance = 200.0
_ = w.colored_mesh
hdist = w.frequency_spacing_hypot_distance
intervals = w.real_freq_max / w.frequency_hours
assert w.mesh_radius == pytest.approx(intervals * hdist, abs=1e-10)
# Add calmrose
w.show_zeros = True
zero_dist = w._zero_mesh_radius
_ = w.colored_mesh
hdist = w.frequency_spacing_hypot_distance
intervals = w.real_freq_max / w.frequency_hours
assert w.mesh_radius == pytest.approx(zero_dist + (intervals * hdist))
# Test size with windrose from actual epw data
epw_path = os.path.join(os.getcwd(), 'tests/fixtures/epw/chicago.epw')
epw = EPW(epw_path)
w = WindRose(epw.wind_direction, epw.wind_speed, 3)
all_legends = []
all_title = []
all_calm_hours = []
all_histograms = []
# Calculate _max_freq_lines_ if it's not already set, to use to
# determine spacing for multiple plots.
if len(_data) > 1 and _max_freq_lines_ is None:
max_freqs = []
for i, _data_item in enumerate(_data):
win_dir = _wind_direction
w = WindRose(win_dir, _data_item, _dir_count_)
if _freq_hours_ is not None:
w.frequency_hours = _freq_hours_
if _freq_dist_ is not None:
w.frequency_spacing_distance = _freq_dist_
max_freqs.append(w.frequency_intervals_compass)
_max_freq_lines_ = max(max_freqs)
# Plot the windroses
for i, speed_data in enumerate(_data):
# Make the windrose
win_dir = _wind_direction
windrose = WindRose(win_dir, speed_data, _dir_count_)
if len(legend_par_) > 0:
try: # sense when several legend parameters are connected
lpar = legend_par_[i]
except IndexError:
lpar = legend_par_[-1]
def test_histogram_data_nested():
# Testing vals
dir_vals = [0, 0, 0, 0, 10, 10, 10, 85, 90, 90, 90, 95, 170, 285, 310]
spd_vals = [0, 0, 0, 0, 1, 145, 189, 15, 10, 150, 299, 259, 100, 5, 301]
# Make into fake data collections
a_per = AnalysisPeriod(6, 21, 12, 6, 21, 13)
dates = [DateTime(6, 21, i) for i in range(len(dir_vals))]
spd_header = Header(Speed(), 'm/s', a_per)
dir_header = Header(GenericType('Direction', 'deg'), 'deg', a_per)
spd_data = HourlyDiscontinuousCollection(spd_header, spd_vals, dates)
dir_data = HourlyDiscontinuousCollection(dir_header, dir_vals, dates)
# Init complex dir set divided by 4, and 2 hourly intervals
w = WindRose(dir_data, spd_data, 4)
w.frequency_hours = 2
w.legend_parameters.segment_count = 7
# Bin values to divide into 6 intervals = 10 - 310 = 300 / 6 = 50 m/s
# intervals: [1-50, 51-100, 101-150, 151-200, 201-250, 251-300, 301-350]
#
# each frequency interval = 1/6 ~ 0.166 of total speed
# 315-45: [1, 145, 189]; 3 bands [0-49, 100-149, 150-199]
# 45-135: [15, 10, 150, 299, 259]; 3 bands, [0-49, 150-199,, 250-299]
# 135-225: [100]; 1 bands, [100-149]
# 225-315: [5, 300]; 2 bands, [0-49, 300, 249]
# interval_num: [3, 3, 1, 2]
chk_histstack = [
[[1], [], [145], [189], [], []], # 0-49, 100-149, 150-199
[[10, 15], [], [150], [], [], [259, 299]], # 0-49, 150-199,, 250-299
[[], [100], [], [], [], []], # 100-149
[[5], [], [], [], [], [301]]] # 0-49, 300-349
# Testing
speeds = [val for bin in w.histogram_data for val in bin]
min_speed, max_speed = min(speeds), max(speeds)
histstack, bins = WindRose._histogram_data_nested(
w.histogram_data, (min_speed, max_speed), w.legend_parameters.segment_count)
# Check
assert len(chk_histstack) == len(histstack)
for cbins, bins in zip(chk_histstack, histstack):
assert len(cbins) == len(bins)
for cbin, bin in zip(cbins, bins):
assert len(cbin) == len(bin)
for cval, val in zip(cbin, bin):
assert abs(cval - val) <= 1e-10, (cval, val)
# Check with zeros
w.show_zeros = True
w.frequency_hours = 1.0
w.frequency_spacing_distance = 25.0
hypot_dist = w.frequency_spacing_hypot_distance
assert abs(w._zero_mesh_radius - hypot_dist) < 1e-10
# Check with zeros 2
# Testing vals
dir_vals = [0, 0, 0, 0, 0, 0, 10, 10, 10, 85, 90, 90, 90, 95, 170, 285, 310]
spd_vals = [0, 0, 0, 0, 0, 0, 1, 145, 189, 15, 10, 150, 299, 259, 100, 5, 301]
# Make into fake data collections
a_per = AnalysisPeriod(6, 21, 12, 6, 21, 13)
dates = [DateTime(6, 21, i) for i in range(len(dir_vals))]
spd_header = Header(Speed(), 'm/s', a_per)
dir_header = Header(GenericType('Direction', 'deg'), 'deg', a_per)
spd_data = HourlyDiscontinuousCollection(spd_header, spd_vals, dates)
dir_data = HourlyDiscontinuousCollection(dir_header, dir_vals, dates)
# Init complex dir set divided by 4, and 2 hourly intervals
w = WindRose(dir_data, spd_data, 4)
w.show_zeros = True
w.frequency_hours = 1.0
w.frequency_spacing_distance = 25.0
hypot_dist = w.frequency_spacing_hypot_distance * 1.5
assert abs(w._zero_mesh_radius - hypot_dist) < 1e-10
