def crnsong_01():
parser = crnparsers.HourlyCrnParser()
# Get six stations that pretty much cover CONUS
stations = parser.find_stations(('Darrington', 'Barbara', 'Northgate', 'Port Aransas', 'Old Town', 'Brunswick'))
print stations
fields = set(('T_CALC', 'SOIL_TEMP_10', 'SOIL_TEMP_50', 'SOLARAD', 'P_CALC'))
#fields = set(('T_CALC', 'SOLARAD', 'SOIL_TEMP_10', 'SOIL_TEMP_50'))
years = range(2008, 2013)
doc = parser.parse(stations, years, fields)
assert len(doc) == len(stations)
doc.combine_all_ranges()
# MIDI output
mrenderer = MidiCCRenderer(sample_rate=24) #24 is the natural fit.
sine_to_midi_map = {'T_CALC': 74, 'SOIL_TEMP_10': 75, 'SOIL_TEMP_50' : 76, 'SOLARAD' : 77, 'P_CALC' : 78} # sine to cc# # 1 is mod wheel, for bowing using the Serenade reaktor patch
#sine_to_midi_map = {'T_CALC': 74, 'SOLARAD': 75, 'SOIL_TEMP_10': 76, 'SOIL_TEMP_50' : 77}
transformed_doc = doc.transform(sine_to_midi_map, mrenderer)
# Create graph
vrenderer = LineGraphRenderer()
# No mapping because LineGraphRenderer doesn't need one.
vrenderer.render(transformed_doc, showplot=True, outfile='/tmp/test.svg')
# Output MIDI
mrenderer.render(transformed_doc, output_file='t.mid')
def crnsong_01():
parser = crnparsers.HourlyCrnParser()
# Get six stations that pretty much cover CONUS
stations = parser.find_stations(('Darrington', 'Barbara', 'Northgate',
'Port Aransas', 'Old Town', 'Brunswick'))
print stations
fields = set(
('T_CALC', 'SOIL_TEMP_10', 'SOIL_TEMP_50', 'SOLARAD', 'P_CALC'))
#fields = set(('T_CALC', 'SOLARAD', 'SOIL_TEMP_10', 'SOIL_TEMP_50'))
years = range(2008, 2013)
doc = parser.parse(stations, years, fields)
assert len(doc) == len(stations)
doc.combine_all_ranges()
# MIDI output
mrenderer = MidiCCRenderer(sample_rate=24) #24 is the natural fit.
sine_to_midi_map = {
'T_CALC': 74,
'SOIL_TEMP_10': 75,
'SOIL_TEMP_50': 76,
'SOLARAD': 77,
'P_CALC': 78
} # sine to cc# # 1 is mod wheel, for bowing using the Serenade reaktor patch
#sine_to_midi_map = {'T_CALC': 74, 'SOLARAD': 75, 'SOIL_TEMP_10': 76, 'SOIL_TEMP_50' : 77}
transformed_doc = doc.transform(sine_to_midi_map, mrenderer)
# Create graph
vrenderer = LineGraphRenderer()
# No mapping because LineGraphRenderer doesn't need one.
vrenderer.render(transformed_doc, showplot=True, outfile='/tmp/test.svg')
# Output MIDI
mrenderer.render(transformed_doc, output_file='t.mid')
def test_midi_renderer_01():
parser = MultiSineDictParser()
# Generate some raw data
sinelist = []
for i in range(3):
sines = generate_sines(3, 120, factor=i)
sinelist.append(sines)
doc = parser.parse(sinelist)
doc.sample_rate = 5
renderer = MidiCCRenderer()
sine_to_midi_map = {0: 74, 1: 75, 2: 76} # sine to cc#
transformed_doc = doc.transform(sine_to_midi_map, renderer)
renderer.render(transformed_doc, output_file='/tmp/t.mid')
def build_data():
parser = GriddedDataParser()
doc = parser.parse()
doc.resample(.1403) # Trial and error to get 30 min of data
# renderer = LineGraphRenderer()
# plot = renderer.render(doc, showplot=True, render_separate=True)
# Produce MIDI data
renderer = MidiCCRenderer()
# divide 20 by 1.782
renderer.tempo = 20
var_to_midi_map = {'air': 74, 'prate': 75, 'rhum': 76, 'wspd': 77}
transformed_doc = doc.transform(var_to_midi_map, renderer)
renderer.render(
transformed_doc,
output_file=
'/Users/egg/Documents/Work In Progress/geothermophone/midi/geothermophone.mid'
)
def build_data():
parser = GriddedDataParser()
doc = parser.parse()
doc.resample(.1403) # Trial and error to get 30 min of data
# renderer = LineGraphRenderer()
# plot = renderer.render(doc, showplot=True, render_separate=True)
# Produce MIDI data
renderer = MidiCCRenderer()
# divide 20 by 1.782
renderer.tempo = 20
var_to_midi_map = {'air': 74,
'prate': 75,
'rhum': 76,
'wspd': 77}
transformed_doc = doc.transform(var_to_midi_map, renderer)
renderer.render(transformed_doc,
output_file='/Users/egg/Documents/Work In Progress/geothermophone/midi/geothermophone.mid')
def midi(doc):
renderer = MidiCCRenderer()
sine_to_midi_map = {'LAT': 74, 'LON': 75, 'TEMP': 76} # sine to cc#
transformed_doc = doc.transform(sine_to_midi_map, renderer)
renderer.render(transformed_doc, output_file='output.mid')
