devtool edits

devtools/func__paramremap.py

@@ -0,0 +1,85 @@
+
+import chardet
+import numpy as np
+import os 
+
+dt_cvpj = np.dtype([
+		('paramid', np.str_, 32),
+		('extid', np.str_, 32),
+		('def_one', np.float64), 
+		('def', np.float64), 
+		('min', np.float64), 
+		('max', np.float64), 
+		('mathtype', np.str_, 3),
+		('mathval', np.float64), 
+		('visname', np.str_, 64)
+		])
+
+dt_vst2 = np.dtype([
+		('paramnum', np.short),
+		('visname', np.str_, 16)
+		])
+
+dt_vst3 = np.dtype([
+		('paramnum', np.short),
+		('visname', np.str_, 24)
+		])
+
+class paramremap:
+	def __init__(self, filename):
+		self.cvpj = np.zeros(0, dtype=dt_cvpj)
+		self.vst2 = np.zeros(0, dtype=dt_vst2)
+		self.vst3 = np.zeros(0, dtype=dt_vst3)
+		if os.path.exists(filename):
+			with open(filename, 'rb') as csvfile:
+				csvdata = csvfile.read()
+				csvcharset = chardet.detect(csvdata)['encoding']
+				csvtext = csvdata.decode(csvcharset).splitlines()
+
+				if len(csvtext)>2:
+					self.cvpj = np.zeros(len(csvtext)-2, dtype=dt_cvpj)
+					self.vst2 = np.zeros(len(csvtext)-2, dtype=dt_vst2)
+					self.vst3 = np.zeros(len(csvtext)-2, dtype=dt_vst3)
+
+					self.cvpj['min'] = 0
+					self.cvpj['max'] = 1
+					self.cvpj['mathtype'] = 'lin'
+					self.cvpj['mathval'] = 1
+					self.vst2['paramnum'] = -1
+					self.vst3['paramnum'] = -1
+
+					self.usedparamnames = {'cvpj': [],'vst2': [],'vst3': []}
+
+					for count, row_unsep in enumerate(csvtext):
+						splitsep = row_unsep.split(',')
+						if count == 0: 
+							data_exttypes = splitsep
+
+						elif count == 1: 
+							data_typenames = splitsep
+							data_len = len(data_exttypes)
+							for n,v in enumerate(data_typenames):
+								self.usedparamnames[data_exttypes[n]].append(v)
+						else:
+							numparam = count-2
+							for x in range(max(data_len, len(splitsep))):
+								extname = data_exttypes[x]
+								dataname = data_typenames[x]
+								dataval = splitsep[x]
+
+								if dataname in ['def_one','def','min','max']: dataval = float(dataval)
+								if dataname == 'paramnum': dataval = float(dataval)
+								if extname == 'cvpj': self.cvpj[numparam][dataname] = dataval
+								if extname == 'vst2': self.vst2[numparam][dataname] = dataval
+								if extname == 'vst3': self.vst3[numparam][dataname] = dataval
+
+					if 'def' not in self.usedparamnames['cvpj']:
+						mulvals = self.cvpj['max']-self.cvpj['min']
+						self.cvpj['def'] = np.asarray(self.cvpj['def_one'], dtype=np.float64)
+						self.cvpj['def'] *= mulvals
+						self.cvpj['def'] += self.cvpj['min']
+					elif 'def_one' not in self.usedparamnames['cvpj']:
+						mulvals = self.cvpj['max']-self.cvpj['min']
+						self.cvpj['def_one'] = np.asarray(self.cvpj['def_one'], dtype=np.float64)
+						self.cvpj['def_one'] -= self.cvpj['min']
+						self.cvpj['def_one'] /= mulvals

devtools/remap_to_dset.py

@@ -1,95 +1,12 @@
 import os 
 import sys
 
+import func__paramremap
 dpath_befr = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..')
 relpath = os.path.abspath(dpath_befr)
 sys.path.append(relpath)
 from objects.datastorage import dataset
 
-import chardet
-import numpy as np
-
-dt_cvpj = np.dtype([
-		('paramid', np.str_, 32),
-		('extid', np.str_, 32),
-		('def_one', np.float64), 
-		('def', np.float64), 
-		('min', np.float64), 
-		('max', np.float64), 
-		('mathtype', np.str_, 3),
-		('mathval', np.float64), 
-		('visname', np.str_, 64)
-		])
-
-dt_vst2 = np.dtype([
-		('paramnum', np.short),
-		('visname', np.str_, 16)
-		])
-
-dt_vst3 = np.dtype([
-		('paramnum', np.short),
-		('visname', np.str_, 24)
-		])
-
-class paramremap:
-	def __init__(self, filename):
-		self.cvpj = np.zeros(0, dtype=dt_cvpj)
-		self.vst2 = np.zeros(0, dtype=dt_vst2)
-		self.vst3 = np.zeros(0, dtype=dt_vst3)
-		if os.path.exists(filename):
-			with open(filename, 'rb') as csvfile:
-				csvdata = csvfile.read()
-				csvcharset = chardet.detect(csvdata)['encoding']
-				csvtext = csvdata.decode(csvcharset).splitlines()
-
-				if len(csvtext)>2:
-					self.cvpj = np.zeros(len(csvtext)-2, dtype=dt_cvpj)
-					self.vst2 = np.zeros(len(csvtext)-2, dtype=dt_vst2)
-					self.vst3 = np.zeros(len(csvtext)-2, dtype=dt_vst3)
-
-					self.cvpj['min'] = 0
-					self.cvpj['max'] = 1
-					self.cvpj['mathtype'] = 'lin'
-					self.cvpj['mathval'] = 1
-					self.vst2['paramnum'] = -1
-					self.vst3['paramnum'] = -1
-
-					self.usedparamnames = {'cvpj': [],'vst2': [],'vst3': []}
-
-					for count, row_unsep in enumerate(csvtext):
-						splitsep = row_unsep.split(',')
-						if count == 0: 
-							data_exttypes = splitsep
-
-						elif count == 1: 
-							data_typenames = splitsep
-							data_len = len(data_exttypes)
-							for n,v in enumerate(data_typenames):
-								self.usedparamnames[data_exttypes[n]].append(v)
-						else:
-							numparam = count-2
-							for x in range(max(data_len, len(splitsep))):
-								extname = data_exttypes[x]
-								dataname = data_typenames[x]
-								dataval = splitsep[x]
-
-								if dataname in ['def_one','def','min','max']: dataval = float(dataval)
-								if dataname == 'paramnum': dataval = float(dataval)
-								if extname == 'cvpj': self.cvpj[numparam][dataname] = dataval
-								if extname == 'vst2': self.vst2[numparam][dataname] = dataval
-								if extname == 'vst3': self.vst3[numparam][dataname] = dataval
-
-					if 'def' not in self.usedparamnames['cvpj']:
-						mulvals = self.cvpj['max']-self.cvpj['min']
-						self.cvpj['def'] = np.asarray(self.cvpj['def_one'], dtype=np.float64)
-						self.cvpj['def'] *= mulvals
-						self.cvpj['def'] += self.cvpj['min']
-					elif 'def_one' not in self.usedparamnames['cvpj']:
-						mulvals = self.cvpj['max']-self.cvpj['min']
-						self.cvpj['def_one'] = np.asarray(self.cvpj['def_one'], dtype=np.float64)
-						self.cvpj['def_one'] -= self.cvpj['min']
-						self.cvpj['def_one'] /= mulvals
-
 dn = 'magical8bitplug2'
 
 infile = "..\\data_ext\\remap\\%s.csv" % dn
@@ -98,7 +15,7 @@ def __init__(self, filename):
 dataset_cat = out_dset.category_add('plugin')
 
 def create_object(infile, objname):
-	pmap_obj = paramremap(infile)
+	pmap_obj = func__paramremap.paramremap(infile)
 	dataset_object = dataset_cat.objects.create(objname)
 
 	for n, x in enumerate(pmap_obj.cvpj):