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Merge pull request #190 from aglowacki/master
Fix exchange format bugs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,9 @@ | ||
| { | ||
| "redis_host": "hyrule", | ||
| "node_name": "invid", | ||
| "xrf_param_override": | ||
| { | ||
| "dataset_dir": "/home/beams/AGLOWACKI/mdata/2idd_luxi", | ||
| "detector_num": 0 | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,168 @@ | ||
| #!/usr/bin/env python | ||
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| import sys | ||
| import json | ||
| import time | ||
| import random | ||
| import numpy as np | ||
| import pvaccess as pva | ||
| import redis | ||
| import pyxrfmaps as px | ||
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| element_csv_filename = "../reference/xrf_library.csv" | ||
| element_henke_filename = "../reference/henke.xdr" | ||
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| class XRF_Stream_Source(): | ||
| def __init__(self, name, param_override, CHANNEL): | ||
| self.node_name = name | ||
| self.bnode_name = bytes(name, 'utf-8') | ||
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| self.dataset_directory = "/" | ||
| self.dataset_name = "Stream" | ||
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| self.row = 0 | ||
| self.col = 0 | ||
| self.width = 50 | ||
| self.height = 50 | ||
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| # Select fitting routine | ||
| #self.fit_rout = px.fitting.routines.nnls() | ||
| self.fit_rout = px.fitting.routines.roi() | ||
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| # Use Gausian Model | ||
| self.model = px.fitting.models.GaussModel() | ||
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| # Load fit parameters | ||
| self.po = param_override | ||
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| self.channel = pva.Channel(CHANNEL) | ||
| # monitor | ||
| self.channel.monitor(self.monitor) | ||
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| self.sprectra_streamer = px.workflow.SpectraNetStreamer("43434") | ||
| self.sprectra_streamer.set_send_counts(True) | ||
| self.sprectra_streamer.set_send_spectra(False) | ||
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| def init_fit_routine(self, int_spec): | ||
| # Initialize model and fit routine with fit parameters | ||
| self.energy_range = px.get_energy_range(int_spec.size, po.fit_params) | ||
| self.model.update_fit_params_values(po.fit_params) | ||
| self.fit_rout.initialize(model, po.elements_to_fit, energy_range) | ||
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| def config_change_handler(self, msg): | ||
| if msg['data'] == self.bnode_name: | ||
| print(msg) | ||
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| def fit_spec(self, spec, id): | ||
| if spec is not None: | ||
| # create a stream block | ||
| sb = px.StreamBlock(-1, self.row, self.col, self.height, self.width, self.dataset_directory, self.dataset_name) | ||
| sb.init_fitting_blocks( {px.FittingRoutines.ROI: self.fit_rout}, self.po.elements_to_fit) | ||
| #sb.spectra = spec | ||
| sb.fitting_blocks[px.FittingRoutines.ROI] = px.StreamFittingBlock() | ||
| # fit the spectra | ||
| sb.fitting_blocks[px.FittingRoutines.ROI].fit_counts = self.fit_rout.fit_counts(self.model, spec, self.po.elements_to_fit) | ||
| print (self.col, id, sb.fitting_blocks[px.FittingRoutines.ROI].fit_counts) | ||
| self.sprectra_streamer.stream(sb) | ||
| self.col += 1 | ||
| if self.col >= self.width: | ||
| self.col = 0 | ||
| self.row += 1 | ||
| if self.row >= self.height: | ||
| self.row = 0 | ||
| if self.row >= self.height: | ||
| self.row = 0 | ||
| # push to redis | ||
| ## | ||
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| def monitor(self, pv): | ||
| xdim = 0 | ||
| yxim = 0 | ||
| data_arr = None | ||
| print(pv['attribute'][3]) | ||
| if len(pv['dimension']) == 2: | ||
| xdim = pv['dimension'][0]['size'] | ||
| ydim = pv['dimension'][1]['size'] | ||
| if 'shortValue' in pv['value'][0]: | ||
| data_arr = pv['value'][0]['shortValue'].reshape(xdim * ydim, 1).astype(np.float32) # TODO: redo so we get proper dims | ||
| elif 'ushortValue' in pv['value'][0]: | ||
| data_arr = pv['value'][0]['ushortValue'].reshape(xdim * ydim, 1).astype(np.float32) # TODO: redo so we get proper dims | ||
| elif 'intValue' in pv['value'][0]: | ||
| data_arr = pv['value'][0]['intValue'].reshape(xdim * ydim, 1).astype(np.float32) # TODO: redo so we get proper dims | ||
| elif 'uintValue' in pv['value'][0]: | ||
| data_arr = pv['value'][0]['uintValue'].reshape(xdim * ydim, 1).astype(np.float32) # TODO: redo so we get proper dims | ||
| elif 'floatValue' in pv['value'][0]: | ||
| data_arr = pv['value'][0]['floatValue'].reshape(xdim * ydim, 1) # TODO: redo so we get proper dims | ||
| else: | ||
| print(pv['value'][0].keys()) | ||
| #print('Got image: %d' % pv['uniqueId'], xdim, ydim, data_arr[:] ) | ||
| self.fit_spec(data_arr, pv['uniqueId']) | ||
| #'value', 'codec', 'compressedSize', 'uncompressedSize', 'dimension', 'uniqueId', 'dataTimeStamp', 'attribute', 'descriptor', 'alarm', 'timeStamp', 'display' | ||
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| def main(): | ||
| CHANNEL = None | ||
| config_dict = None | ||
| param_override = None | ||
| p = None | ||
| if len(sys.argv) < 2: | ||
| print("Please provide config file as second arg") | ||
| exit(1) | ||
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| print ('Loading json file ', sys.argv[1]) | ||
| with open(sys.argv[1]) as json_file: | ||
| config_dict = json.load(json_file) | ||
| print (config_dict) | ||
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| if config_dict == None: | ||
| print('Error loading json file ', sys.argv[1]) | ||
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| if 'redis_host' in config_dict: | ||
| r = redis.Redis(config_dict['redis_host']) | ||
| # get initial config | ||
| doc = r.json().get('xrf_workers', '$') | ||
| if not config_dict['node_name'] in doc[0]: | ||
| print ('Config not found for ', config_dict['node_name']) | ||
| print (doc) | ||
| exit(1) | ||
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| # subscribe to config_change for live changes | ||
| #p = r.pubsub() | ||
| #p.subscribe(**{'config_change': config_change_handler}) | ||
| # connect to PVA channel | ||
| CHANNEL = str(doc[0][config_dict['node_name']]['PVA']) # 'bdpSimDetector:Pva1:Image' | ||
| print(config_dict['node_name'], CHANNEL) | ||
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| # get param override from redis | ||
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| if CHANNEL == None: | ||
| if 'PVA' in config_dict: | ||
| CHANNEL = config_dict['PVA'] | ||
| else: | ||
| print("Please add 'PVA' to config.json or add a 'redis_host' to get config data from") | ||
| exit(1) | ||
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| if param_override == None: | ||
| if "xrf_param_override" in config_dict: | ||
| config_dict["xrf_param_override"]["dataset_dir"] = config_dict["xrf_param_override"]["dataset_dir"] + '/' | ||
| param_override = px.load_override_params(config_dict["xrf_param_override"]["dataset_dir"], config_dict["xrf_param_override"]["detector_num"], True) | ||
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| # load ref info | ||
| px.load_element_info(element_henke_filename, element_csv_filename) | ||
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| if 'node_name' not in config_dict: | ||
| config_dict['node_name'] = 'node_' + str(random.randint(100,1000)) | ||
| print('Could not find "node_name" in config.json. Using random generated name = ', config_dict['node_name'] ) | ||
| source = XRF_Stream_Source(config_dict['node_name'], param_override, CHANNEL) | ||
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| # loop and check config changes | ||
| for i in range(1000): | ||
| #if p is not None: | ||
| #p.get_message() | ||
| time.sleep(1) | ||
| #time.sleep(1000) | ||
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| if __name__ == '__main__': | ||
| main() | ||
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