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')