Merge pull request #66 from feagi/pre-release

Pre release

embodiments/bluetooth_controller/version.py

@@ -1 +1 @@
-__version__ = 'v1.1.0'
+__version__ = 'v1.2.0'

embodiments/godot-games-controller/version.py

@@ -1 +1 @@
-__version__ = 'v1.1.0'
+__version__ = 'v1.2.0'

embodiments/media_capture_controller/version.py

@@ -1 +1 @@
-__version__ = 'v1.1.0'
+__version__ = 'v1.2.0'

feagi_connector_core/feagi_connector/actuators.py

@@ -181,3 +181,10 @@ def check_convert_gpio_to_input(obtained_data):
         for data_point in obtained_data['gpio_input']:
             input_gpio_data[data_point] = obtained_data['gpio_input'][data_point]
     return input_gpio_data
+
+
+def get_position_data(power, capabilities, device_id):
+    max_input = pns.full_list_dimension['o_spos']['cortical_dimensions'][2]
+    min_output = capabilities['servo']['servo_range'][str(device_id)][0]
+    max_output = capabilities['servo']['servo_range'][str(device_id)][1]
+    return (power / max_input) * (max_output - min_output) + min_output

feagi_connector_core/feagi_connector/feagi_interface.py

@@ -287,12 +287,12 @@ def opu_processor(data):
                         device_id = data_point[0]
                         device_power = data_point[2]
                         processed_opu_data['vision_acuity'][device_id] = device_power
-            if 'o_gpio' in opu_data:
-                if opu_data['o_gpio']:
-                    for data_point in opu_data['o_gpio']:
+            if 'odgpio' in opu_data:
+                if opu_data['odgpio']:
+                    for data_point in opu_data['odgpio']:
                         processed_data_point = block_to_array(data_point)
                         device_id = processed_data_point[0]
-                        device_power = opu_data['o_gpio'][data_point]
+                        device_power = opu_data['odgpio'][data_point]
                         processed_opu_data['gpio'][device_id] = device_power
             if 'oigpio' in opu_data:
                 if opu_data['oigpio']:

feagi_connector_core/feagi_connector/pns_gateway.py

@@ -91,6 +91,38 @@ def grab_geometry():
     return router.fetch_geometry()
 
 
+def fetch_servo_position_size_and_return_percentage(capabilities, current_position, servo_id,
+                                                    flip=False):
+    if full_list_dimension:
+        if 'i_spos' in full_list_dimension:
+            max_input = full_list_dimension['i_spos']['cortical_dimensions'][2]
+            min_output = capabilities['servo']['servo_range'][str(servo_id)][0]
+            max_output = capabilities['servo']['servo_range'][str(servo_id)][1]
+            total_range = max_output - min_output
+            encoder_position = (current_position / total_range) * max_input
+            if flip:
+                data = str(servo_id) + '-0-' + str(int(round(max_input / 2) + encoder_position))
+            else:
+                data = str(servo_id) + '-0-' + str(int(round(max_input / 2) - encoder_position))
+            return data
+    return None  # Just return none to confirm that it's unable to fetch genome information
+
+
+def fetch_servo_motion_sensor_size_and_return_percentage(current_speed, servo_id, max_speed):
+    if full_list_dimension:
+        if 'i_smot' in full_list_dimension:
+            max_input = full_list_dimension['i_smot']['cortical_dimensions'][2]
+            min_output = 0
+            total_range = max_speed - min_output
+            encoder_position = ((current_speed / total_range) * max_input)
+            if encoder_position < 0:
+                data = str(servo_id + 1) + '-0-' + str(int(abs(encoder_position)))
+            else:
+                data = str(servo_id) + '-0-' + str(int(abs(encoder_position)))
+            return data
+    return None  # Just return none to confirm that it's unable to fetch genome information
+
+
 def obtain_opu_data(message_from_feagi):
     """
     It retrieves raw data from FEAGI and then passes the data to the opu_processor, located in
@@ -174,19 +206,11 @@ def eccentricity_control_update(message_from_feagi, capabilities):
         for data_point in message_from_feagi["opu_data"]['ov_ecc']:
             device_id = data_point.split('-')[0]
             if str(device_id) in ['0', '1']:
-                feagi_aptr = (int(data_point.split('-')[-1]))
-                aptr_cortical_size = full_list_dimension['ov_ecc']['cortical_dimensions'][2] - 1
+                intensity_select = (int(data_point.split('-')[-1]))
+                max_depth_of_cortical = full_list_dimension['ov_ecc']['cortical_dimensions'][2] - 1
                 max_range = capabilities['camera']['vision_range'][1]
                 min_range = capabilities['camera']['vision_range'][0]
-                capabilities['camera']["eccentricity_control"][str(device_id)] = int(
-                    ((feagi_aptr / aptr_cortical_size) * (max_range - min_range)) + min_range)
-            # Comment new method out
-            # processed_data_point = feagi.block_to_array(data_point)
-            # device_id = processed_data_point[0]
-            # device_power = message_from_feagi["opu_data"]['ov_ecc'][data_point]
-            # if device_power == 100:
-            #     device_power -= 1
-            # capabilities['camera']['eccentricity_control'][device_id] = device_power
+                capabilities['camera']["eccentricity_control"][str(device_id)] = int(((intensity_select / max_depth_of_cortical) * (max_range - min_range)) + min_range)
     return capabilities
 
 
@@ -198,21 +222,11 @@ def modulation_control_update(message_from_feagi, capabilities):
         for data_point in message_from_feagi["opu_data"]['ov_mod']:
             device_id = data_point.split('-')[0]
             if str(device_id) in ['0', '1']:
-                feagi_aptr = (int(data_point.split('-')[-1]))
-                aptr_cortical_size = full_list_dimension['ov_mod']['cortical_dimensions'][2] - 1
+                intensity_select = (int(data_point.split('-')[-1]))
+                max_depth_of_cortical = full_list_dimension['ov_mod']['cortical_dimensions'][2] - 1
                 max_range = capabilities['camera']['vision_range'][1]
                 min_range = capabilities['camera']['vision_range'][0]
-                capabilities['camera']["modulation_control"][str(device_id)] = int(((feagi_aptr /
-                                                                                aptr_cortical_size) * (
-                                                                                       max_range - min_range)) + min_range)
-        # comment new method out
-        # for data_point in message_from_feagi["opu_data"]['ov_mod']:
-        #     processed_data_point = feagi.block_to_array(data_point)
-        #     device_id = processed_data_point[0]
-        #     device_power = message_from_feagi["opu_data"]['ov_mod'][data_point]
-        #     if device_power == 100:
-        #         device_power -= 1
-        #     capabilities['camera']['modulation_control'][device_id] = device_power
+                capabilities['camera']["modulation_control"][str(device_id)] = int(((intensity_select / max_depth_of_cortical) * (max_range - min_range)) + min_range)
     return capabilities
 
 
@@ -311,14 +325,14 @@ def fetch_vision_turner(message_from_feagi, capabilities):
             if message_from_feagi["opu_data"]["ovtune"]:
                 for data_point in message_from_feagi["opu_data"]['ovtune']:
                     device_id = data_point.split('-')[0]
-                    feagi_aptr = (int(data_point.split('-')[-1]))
-                    aptr_cortical_size = full_list_dimension['ovtune']['cortical_dimensions'][2] - 1
+                    intensity_select = (int(data_point.split('-')[-1]))
+                    max_depth_of_cortical = full_list_dimension['ovtune']['cortical_dimensions'][2] - 1
                     max_range = capabilities['camera']["threshold_range"][1]
                     min_range = capabilities['camera']["threshold_range"][0]
                     if int(device_id) == 1:
-                        capabilities['camera']["percentage_to_allow_data"] = int(((feagi_aptr /aptr_cortical_size) * (10 - 1)) + 1) / 10
+                        capabilities['camera']["percentage_to_allow_data"] = int(((intensity_select / max_depth_of_cortical) * (10 - 1)) + 1) / 10
                     else:
-                        capabilities['camera']["threshold_default"][int(device_id)] = int(((feagi_aptr / aptr_cortical_size) * (max_range - min_range)) + min_range)
+                        capabilities['camera']["threshold_default"][int(device_id)] = int(((intensity_select / max_depth_of_cortical) * (max_range - min_range)) + min_range)
     return capabilities
 
 
@@ -330,6 +344,7 @@ def fetch_threshold_type(message_from_feagi, capabilities):
                 capabilities['camera']["threshold_type"][int(device_id)] = True
     return capabilities
 
+
 def fetch_mirror_opu(message_from_feagi, capabilities):
     if "ovflph" in message_from_feagi["opu_data"]:
         if message_from_feagi["opu_data"]["ovflph"]:
@@ -347,31 +362,25 @@ def fetch_enhancement_data(message_from_feagi, capabilities):
                 for data_point in message_from_feagi["opu_data"]['ov_enh']:
                     device_id = int(data_point.split('-')[0])
                     if device_id == 1:
-                        feagi_aptr = (int(data_point.split('-')[-1]))
-                        aptr_cortical_size = full_list_dimension['ov_enh']['cortical_dimensions'][
+                        intensity_select = (int(data_point.split('-')[-1]))
+                        max_depth_of_cortical = full_list_dimension['ov_enh']['cortical_dimensions'][
                                                  2] - 1
                         max_range = 1.4
                         min_range = 0.5
-                        capabilities['camera']["enhancement"][int(device_id)] = float(((feagi_aptr
-                                                                                        / aptr_cortical_size) * (
-                                                                                               max_range - min_range)) + min_range)
+                        capabilities['camera']["enhancement"][int(device_id)] = float(((intensity_select / max_depth_of_cortical) * (max_range - min_range)) + min_range)
                     if device_id == 2:
-                        feagi_aptr = (int(data_point.split('-')[-1]))
-                        aptr_cortical_size = full_list_dimension['ov_enh']['cortical_dimensions'][
+                        intensity_select = (int(data_point.split('-')[-1]))
+                        max_depth_of_cortical = full_list_dimension['ov_enh']['cortical_dimensions'][
                                                  2] - 1
                         max_range = 2.0
                         min_range = 0.8
-                        capabilities['camera']["enhancement"][int(device_id)] = float(((feagi_aptr
-                                                                                        / aptr_cortical_size) * (
-                                                                                               max_range - min_range)) + min_range)
+                        capabilities['camera']["enhancement"][int(device_id)] = float(((intensity_select/ max_depth_of_cortical) * (max_range - min_range)) + min_range)
                     if device_id == 0:
-                        feagi_aptr = (int(data_point.split('-')[-1]))
-                        aptr_cortical_size = full_list_dimension['ov_enh']['cortical_dimensions'][2]
+                        intensity_select = (int(data_point.split('-')[-1]))
+                        max_depth_of_cortical = full_list_dimension['ov_enh']['cortical_dimensions'][2]
                         max_range = 100
                         min_range = -100
-                        capabilities['camera']["enhancement"][int(device_id)] = float(((feagi_aptr
-                                                                                        / aptr_cortical_size) * (
-                                                                                               max_range - min_range)) + min_range)
+                        capabilities['camera']["enhancement"][int(device_id)] = float(((intensity_select/ max_depth_of_cortical) * (max_range - min_range)) + min_range)
     return capabilities
 
 
@@ -407,12 +416,14 @@ def create_runtime_default_list(list, capabilities):
                 "threshold_name": 0,  # Binary_threshold as a default
                 "mirror": True,  # flip the image
                 "blink": [],  # cv2 ndarray raw data of an image. Controlled by blink OPU in genome
-                "eccentricity_control": {'0': 1, '1': 1},  # Controlled by eccentricity_control in genome
-                "modulation_control": {'0': 99, '1': 99},  # Controlled by modulation_control in genome
+                "eccentricity_control": {'0': 1, '1': 1},
+                # Controlled by eccentricity_control in genome
+                "modulation_control": {'0': 99, '1': 99},
+                # Controlled by modulation_control in genome
                 "vision_range": [1, 99],  # min, max
                 "size_list": [],  # To get the size in real time based on genome's change/update
                 "enhancement": {},  # Enable ov_enh OPU on inside the genome
-                "percentage_to_allow_data" : 0.5 # this will be percentage for the full data.
+                "percentage_to_allow_data": 0.5  # this will be percentage for the full data.
                 # Currently set to 0.5 to allow data go through otherwise discard it fully.
             }
         }
@@ -436,7 +447,8 @@ def camera_config_update(list, capabilities):
         if "threshold_default" in capabilities['camera']:
             list['camera']['threshold_default'] = capabilities['camera']['threshold_default']
         if "percentage_to_allow_data" in capabilities['camera']:
-            list['camera']['percentage_to_allow_data'] = capabilities['camera']['percentage_to_allow_data']
+            list['camera']['percentage_to_allow_data'] = capabilities['camera'][
+                'percentage_to_allow_data']
 
 
 def feagi_listener(feagi_opu_channel):

feagi_connector_core/feagi_connector/sensors.py

@@ -67,3 +67,14 @@ def add_agent_status(status, message_to_feagi, agent_settings):
     else:
         message_to_feagi["data"]['connected_agents'] = []
     return message_to_feagi
+
+
+def convert_sensor_to_ipu_data(min_output, max_output, raw_data, pin_number):
+    if pns.full_list_dimension:
+        if 'iagpio' in pns.full_list_dimension:
+            max_input = pns.full_list_dimension['iagpio']['cortical_dimensions'][2] - 1
+            total_range = max_output - min_output
+            encoder_position = (raw_data / total_range) * max_input
+            data = str(pin_number) + '-0-' + str(int(round(encoder_position)))
+            return data
+    return None

feagi_connector_core/setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = feagi_connector
-version = 0.0.11
+version = 0.0.12
 author = Neuraville Inc.
 author_email = info@feagi.org
 description = Feagi agent to work with general and simulation robots