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# Generated by Django 2.2.4 on 2020-01-16 20:19
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('shop', '0006_product_likes'),
]
operations = [
migrations.AlterField(
model_name='product',
name='likes',
field=models.ManyToManyField(blank=True, related_name='prod_likes', to=settings.AUTH_USER_MODEL),
),
]
|
import sys
def cnt (A, X, R, L):
# Write your code here
out = []
for (l,r,x) in zip (L, R, X):
t = 0
for i in range (l-1, r):
if x % A[i] == 0:
t += 1
out.append (t)
return out
# N = int(input())
# A = list(map(int, input().split()))
# Q = int(input())
# L = list(map(int, input().split()))
# R = list(map(int, input().split()))
# X = list(map(int, input().split()))
N = int(sys.stdin.readline())
A = list(map(int, sys.stdin.readline().split()))
Q = int(sys.stdin.readline())
L = list(map(int, sys.stdin.readline().split()))
R = list(map(int, sys.stdin.readline().split()))
X = list(map(int, sys.stdin.readline().split()))
out_ = cnt(A, X, R, L)
print (' '.join(map(str, out_)))
|
# 题目 暂停一秒输出。
# 程序分析 使用 time 模块的 sleep() 函数。
# Python 编程中使用 time 模块可以让程序休眠，
# 具体方法是time.sleep(秒数)，其中"秒数"以秒为单位，可以是小数，0.1秒则代表休眠100毫秒。
import time
for i in range(4):
print(str(int(time.time()))[-2:])
time.sleep(1)
|
#!/usr/bin/python
if __name__ == '__main__':
N = int(raw_input())
numbers = []
for i in range(0, N):
tmp = raw_input()
command, value = tmp.split(' ')
if command == 'a':
numbers.append(int(value))
else:
try:
numbers.remove(int(value))
except ValueError:
print "Wrong!"
continue
if len(numbers) == 0:
print "Wrong!"
continue
numbers.sort()
if len(numbers) % 2 == 0:
l = len(numbers) / 2 - 1
r = len(numbers) / 2
median = (numbers[l] + 0 + numbers[r]) * 0.5
if median.is_integer():
print int(median)
else:
print median
else:
print (numbers[(len(numbers) - 1) / 2])
|
import configparser
import os
def get_creds(collection: str, database="SpotiBot"):
config = configparser.ConfigParser()
config.read(os.path.join(os.getcwd(), "mongo_creds.cfg"))
conn_str = (
f"mongodb+srv://{config.get('mongo', 'USERNAME')}:"
f"{config.get('mongo', 'PASSWORD')}@"
f"{config.get('mongo', 'DATABASE')}-gkkvg.mongodb"
f".net/{config.get('mongo', 'COLLECTION')}?"
f"retryWrites=true&w=majority"
)
# TODO: Figure out why feeding the collection name as arguments results
# in an invalid collection
# conn_str = f"mongodb+srv://{config.get('mongo', 'USERNAME')}:" \
# f"{config.get('mongo', 'PASSWORD')}@" \
# f"{config.get('mongo', 'DATABASE')}-gkkvg.mongodb" \
# f".net/{collection}?" \
# f"retryWrites=true&w=majority"
# conn_str = f"mongodb+srv://{config.get('mongo', 'USERNAME')}:" \
# f"{config.get('mongo', 'PASSWORD')}@" \
# f"SpotiBot-gkkvg.mongodb" \
# f".net/{collection}?" \
# f"retryWrites=true&w=majority"
return conn_str
|
import sys, os, shutil
from datetime import date
from pyspark.sql import SparkSession
from pyspark.sql.functions import to_date
from pyspark.sql.types import StructType, StructField, StringType, IntegerType, TimestampType, DoubleType
test_data = "C:\\Telco Relax\\Input_test\\"
prod_data = "C:\\Telco Relax\\Input\\"
spark = SparkSession.builder.master("local[1]") \
.appName('Telco_Relax_ETL') \
.getOrCreate()
spark.conf.set(
"",
"")
data = spark.read.options(inferSchema='True', delimiter=',').csv(prod_data + "*.csv")
desired_schema = StructType([
StructField("customer_id", IntegerType(), True),
StructField("event_start_time", TimestampType(), True),
StructField("event_type", StringType(), True),
StructField("rate_plan_id", IntegerType(), True),
StructField("billing_flag_1", IntegerType(), True),
StructField("billing_flat_2", IntegerType(), True),
StructField("duration", IntegerType(), True),
StructField("charge", DoubleType(), True),
StructField("month", StringType(), True)
])
#checking schema data types if they match
types_desired = [f.dataType for f in desired_schema.fields]
types_actual = [f.dataType for f in data.schema.fields]
#print(types_desired)
#print(types_actual)
if types_desired != types_actual:
sys.exit("Schema validation failed")
elif data.count == 0:
sys.exit("File is empty")
else:
print("Schema and file validation OK")
print(data.count())
print(data.printSchema())
data_with_schema = data.withColumnRenamed("_c0", "customer_id").withColumnRenamed("_c1", "event_start_time").withColumnRenamed("_c2", "event_type") \
.withColumnRenamed("_c3", "rate_plan_id").withColumnRenamed("_c4", "billing_flag_1").withColumnRenamed("_c5", "billing_flat_2")\
.withColumnRenamed("_c6", "duration").withColumnRenamed("_c7", "charge").withColumnRenamed("_c8", "month")
#parsin date from event start time so it would be possible to partition by it
data_with_date = data_with_schema.withColumn("date", to_date("event_start_time", "yyyy-MM-dd"))
data_with_date.repartition("date", "event_type").write.mode("append").partitionBy("date", "event_type").format("parquet").save("wasbs://datalake@telcorelaxblob01.blob.core.windows.net/data")
# #move loaded file to archive folder
dest = "C:\\Telco Relax\\Archive\\processed_" + date.today().strftime('%Y-%m-%d')
files = os.listdir(prod_data)
for f in files:
shutil.move(prod_data + f, dest + f)
|
# ДЗ:
# 1. Создать функцию, которая выводит на экран цифру, введенную пользоватлем в консоли.
# 2. Написать программу, которая считает 5 значений, введенных пользователем из консоли, сохранит их в список
# затем передаст значения в фукцию, которая выводит на экран сумму значений списка.
# 3. Написать программу, которая:
# - выводит следующее меню на экран
# 1. Ввести значения а и b
# 2. Умножить значения а и b
# 3. Делить а на b
# 4. Выход
# - реализует кажду опцию как фукцию
# - реализует все ошибки и исключения.
|
import datetime
pessoa = dict()
ano_atual = datetime.datetime.now().year
pessoa['nome'] = str(input('Nome: '))
pessoa['idade'] = ano_atual-int(input('Ano de nascimento: '))
pessoa['ctps'] = int(input('Carteira de trabalho (0 não tem): '))
if((pessoa['ctps']) != 0):
pessoa['contratado'] = int(input('Ano de contratação: '))
pessoa['salario'] = float(input('Salário: R$'))
if((ano_atual-pessoa['contratado']) < 35):
pessoa['aposentadoria'] = (35-(ano_atual-pessoa['contratado']))+pessoa['idade']
else:
pessoa['aposentadoria'] = 'aposentado'
print('-=' * 40)
print(pessoa)
for k, v in pessoa.items():
print(f'{k}: {v}')
|
# -*- coding: UTF-8 -*-
import sys
from System import *
from collections import deque
from System.Math import *
from processing.classification.types import *
from processing.segmentation.connected import *
from processing.contours.psweeping import *
def check_for_circle(segments, cmask, cline, sline, info, window = 3, minSize = 30):
(fy,fx) = cline[0]
(counts,xmins, xmaxs, ymins, ymaxs, meansx, meansy) = info
seg = segments[fy,fx]
if counts[seg] < minSize:
return False
(my,mx) = (meansy[seg], meansx[seg])
print ("Seg: {}".format(seg))
distances = {}
for (py,px) in cline:
d = int(round(distance(mx, my, px, py)))
c = distances.get(d)
if c == None:
c = 1
else:
c += 1
distances[d] = c
ldistances = distances.keys()
minDist = min(ldistances)
maxDist = max(ldistances)
print ("seg: {}, minDist: {}, maxDist: {}".format(seg, minDist, maxDist))
return (maxDist - minDist) <= window
def check_for_line(segments, cmask, cline, sline, info, window = 5, minSize = 20):
(counts, xmins, xmaxs, ymins, ymaxs, meansx, meansy) = info
(py,px) = cline[0]
seg = segments[py,px]
if counts[seg] < minSize:
return False
xmin = xmins[seg]
ymin = ymins[seg]
xmax = xmaxs[seg]
ymax = ymaxs[seg]
cyMax = 0
for i in range(ymin, ymax+1):
c = 0
for j in range(xmin, xmax+1):
if segments[i,j] == seg:
c += 1
if c > cyMax:
cyMax = c
cxMax = 0
for j in range(xmin, xmax+1):
c = 0
for i in range(ymin, ymax+1):
if segments[i,j] == seg:
c += 1
if c > cxMax:
cxMax = c
return cyMax <= window or cxMax <= window
def classificate_shape(segments, cmask, cline, sline, info):
if check_for_circle(segments, cmask, cline, sline, info):
print ("Circle detected")
elif check_for_line(segments, cmask, cline, sline, info):
print ("Line detected")
vertices = []
for (py,px) in sline:
vertices.append(Point(px,py))
return Polygon(vertices)
def classificate_shapes(segments, cmask, clines, slines):
info = calculate_segment_parameters(segments)
shapes = {}
for (seg,sline) in slines.items():
shapes[seg] = classificate_shape(segments, cmask,
clines[seg], sline, info)
return shapes
|
# Copyright (c) 2021 kamyu. All rights reserved.
#
# Google Code Jam 2021 Round 1C - Problem A. Closest Pick
# https://codingcompetitions.withgoogle.com/codejam/round/00000000004362d7/00000000007c0f00
#
# Time: O(NlogN)
# Space: O(N)
#
def closest_pick():
N, K = map(int, raw_input().strip().split())
P = sorted(set(map(int, raw_input().strip().split())))
result = prev_max = P[0]-1 # one or two in the first interval
for i in xrange(1, len(P)):
result = max(result, prev_max+(P[i]-P[i-1])//2, P[i]-P[i-1]-1) # one or two in this interval
prev_max = max(prev_max, (P[i]-P[i-1])//2)
return float(max(result, prev_max+(K-P[-1])))/K # one or two in the last interval
for case in xrange(input()):
print 'Case #%d: %s' % (case+1, closest_pick())
|
from flask import render_template, flash, url_for, redirect, request, session
from .. import db, bcrypt
from ..models import User
#from app.user.forms import AjouteruserForm, PassuserForm, EditeruserForm
from flask_login import login_user, current_user, logout_user, login_required
from . import main
@main.route('/administration', methods=['GET', 'POST'])
@login_required
def dashboard():
title='Dashboard | Kivu Exchange'
return render_template('main/main.html', title=title)
@main.route('/configuration', methods=['GET', 'POST'])
@login_required
def config():
title='Dashboard | Kivu Exchange'
return render_template('main/conf.html', title=title)
@main.route('/conf_produit', methods=['GET', 'POST'])
@login_required
def configpro():
title='Dashboard | Kivu Exchange'
return render_template('main/confpro.html', title=title)
|
from django.contrib.auth.models import AbstractUser
from django.db import models
class User(AbstractUser):
name = models.CharField('이름', max_length=100)
class Todo(models.Model):
created = models.DateTimeField(auto_now_add=True)
text = models.CharField(max_length=200)
title = models.TextField(max_length=50)
success = models.BooleanField(default=False)
user = models.ForeignKey(User, on_delete=models.CASCADE)
status = models.BooleanField(default=False)
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
# File: w2v_to_numpy.py
# Convert binary W2V file to
import sys, struct, re
import cPickle, gzip
import numpy as np
from w2v_to_numpy import W2VLoader
def listFromFile(fname):
ret = []
f = open(fname, 'r')
for l in f:
l = l.decode('utf-8').strip()
ret.append(l)
f.close()
return ret
if __name__ == '__main__':
rng = np.random.RandomState(1234)
# Open file and read header information
loader = W2VLoader(sys.argv[1])
vcbName = sys.argv[2]
outName = sys.argv[3]
# optional suffixes
suffix_reStr = r'(' + '|'.join(sys.argv[4].decode('utf-8').split()) + ')$' if len(sys.argv) > 4 else ''
suffix_regex = re.compile(suffix_reStr)
rndhi = 0.5 / loader.embSize
rndlo = -rndhi
usedVcb = listFromFile(vcbName)
embTab = []
for v in usedVcb:
if suffix_regex.search(v):
v_s = suffix_regex.sub('', v) # stripped of allowed suffix
try:
embTab.append(loader.M[loader.wordID[v_s]])
except KeyError:
embTab.append(rng.uniform(rndlo, rndhi, (loader.embSize,)))
else:
try:
embTab.append(loader.M[loader.wordID[v]])
except KeyError:
embTab.append(rng.uniform(rndlo, rndhi, (loader.embSize,)))
print v.encode('utf-8')
M = np.memmap('{}.mat.mmap'.format(outName), dtype='float32', mode='w+', shape=(len(embTab), loader.embSize))
M[:] = np.asarray(embTab)
# Close the file and pickle embedding
M.flush()
del M
|
from phantomjs import phantomjs
import logging
import io
import flask
# Flash application context
app = flask.Flask(__name__)
# Setup logging
logging.getLogger().setLevel(logging.INFO)
@app.route('/')
def welcome():
"""
:return: The Wrender homepage
"""
return 'Wrender'
@app.route('/ping')
def ping():
"""
:return: a simple message to verify the system is running.
"""
return 'pong'
@app.route('/render')
def render():
"""
Tries to retrieve the HAR with rendered images, returning a 500 if timing out.
If data is POST'd it expects a string-representation of a list of selectors, e.g.:
"[\":root\"]"
"""
url = flask.request.args.get('url')
app.logger.info("Got URL: %s" % url)
#
selectors = flask.request.args.get('selectors', ':root')
app.logger.debug("Got selectors: %s" % selectors)
#
warc_prefix = flask.request.args.get('warc_prefix', 'wrender')
app.logger.debug("Got WARC prefix: %s" % warc_prefix)
#
include_rendered = flask.request.args.get('include_rendered', False)
app.logger.debug("Got include_rendered: %s" % include_rendered)
#
show_screenshot = flask.request.args.get('show_screenshot', False)
app.logger.debug("Got show_screenshot: %s" % show_screenshot)
#
if show_screenshot:
return flask.send_file(io.BytesIO(
phantomjs.get_har_with_image(url, selectors, warc_prefix=warc_prefix,
include_rendered=include_rendered, return_screenshot=True)), mimetype='image/png')
else:
return flask.jsonify(phantomjs.get_har_with_image(url, selectors, warc_prefix=warc_prefix,
include_rendered=include_rendered))
|
__version__ = "0.1.0"
# Submodule imports
from . import isis_serial_number
from . import io_controlnetwork
from . import io_gdal
from . import io_json
from . import io_yaml
from . import io_db
from . import io_hdf
from . import utils
from . import examples
from . import data
|
def solve(a,b):
return [a.count(y) for y in b]
'''
Given two arrays of strings, return the number of times each string
of the second array appears in the first array.
Example
array1 = ['abc', 'abc', 'xyz', 'cde', 'uvw']
array2 = ['abc', 'cde', 'uap']
How many times do the elements in array2 appear in array1?
'abc' appears twice in the first array (2)
'cde' appears only once (1)
'uap' does not appear in the first array (0)
Therefore, solve(array1, array2) = [2, 1, 0]
'''
|
import math
import logging
import pylo
tilt_corrector = None
tilt_corrector_reset_event_id = "tilt_corrector_reset"
tilt_corrector_correct_tilt_event_id = "tilt_corrector_correct_tilt"
tilt_corrector_create_event_id = "tilt_corrector_create"
def create_tilt_corrector(controller):
global tilt_corrector, tilt_corrector_reset_event_id, tilt_corrector_correct_tilt_event_id
tilt_corrector = TiltCorrection(controller)
if tilt_corrector_reset_event_id not in pylo.events.series_ready:
pylo.events.series_ready[tilt_corrector_reset_event_id] = tilt_corrector.reset
if tilt_corrector_correct_tilt_event_id not in pylo.events.before_record:
pylo.events.before_record[tilt_corrector_correct_tilt_event_id] = tilt_corrector.correctTilts
if tilt_corrector_create_event_id not in pylo.events.init_ready:
pylo.events.init_ready[tilt_corrector_create_event_id] = create_tilt_corrector
class TiltCorrection:
def __init__(self, controller):
"""Create a new oject"""
self.controller = controller
# for debugging
self.logger = pylo.logginglib.get_logger(self)
self.config_name_general = "tilt-correction"
self.tilt_directions = ("x", "y")
self.correction_types = ("Off", "Automatic", "Manual", "Automatic+Manual")
self.measurememt_variable_ids = list(map(lambda x: x.unique_id,
self.controller.microscope.supported_measurement_variables))
self.tilt_cache_values = {}
for d in self.tilt_directions:
self.tilt_cache_values[d] = {}
self.defineConfigurationOptions()
def _getTiltConfigName(self, direction):
return "{}-{}".format(self.config_name_general, direction)
def defineConfigurationOptions(self, *args, **kwargs):
"""Define the configuration options for the tilt correction before the
program loop is started.
"""
pylo.logginglib.log_debug(self.logger, ("Defining configuration " +
"options for tilt correction "+
"plugin"))
for d in self.tilt_directions:
n = self._getTiltConfigName(d)
self.controller.configuration.addConfigurationOption(
n, "correction-type",
datatype=pylo.Datatype.options(self.correction_types),
default_value=self.correction_types[0],
description=("Enable or disable the tilt correction for " +
"tilts in the {} direction.\n\n" +
"Use off for no correction. Use Automatic for " +
"an automatic correction. Use Manual for a " +
"dialog that will show up and pause the " +
"measurement until the correction is done " +
"manually. Use Automatic+Manual to do the " +
"automatic correction and then show the dialog " +
"to allow manual interaction.").format(d))
self.controller.configuration.addConfigurationOption(
n, "tilt-id",
datatype=pylo.Datatype.options(list(self.measurememt_variable_ids)),
description=("The {} tilt measurement variable id. This " +
"variable is used to tilt in the {} direction. " +
"If this is not given or invalid, the correction " +
"cannot be done automatically.").format(d, d))
for sd in ("x", "y"):
self.controller.configuration.addConfigurationOption(
n, "stage-{}-variable-id".format(sd),
datatype=pylo.Datatype.options(list(self.measurememt_variable_ids)),
description=("The id of the measurement variable to " +
"modify the {} value of the stage. Ignored for " +
"manual correction.").format(sd))
self.controller.configuration.addConfigurationOption(
n, "stage-{}".format(sd), datatype=float, default_value=0,
description=("The stage correction in {sd} direction after " +
"every tilt step in the stage units. Ignored " +
"in manual mode.\n\n" +
"The given value here is the distance from " +
"the feature on the specimen to surveil to " +
"the rotational center. The distance the " +
"stage is moved by {sd}(a)=l_{sd} cos(a) from " +
"the initial point (where a=0°).\n\n" +
"l_{sd} easily be calculated by using two " +
"reference angles with the corresponding {sd} " +
"translation. " +
# this is just wrong
# "For a rough calibration you " +
# "can tilt the sample by 1° in {d} direction " +
# "and measure the moved horizontal distance " +
# "between the two images. Since cos(0°)=1 and " +
# "cos(1°)~1 this is good enough for " +
# "most of the lorentz images."
""
).format(sd=sd, d=d))
def reset(self, *args, **kwargs):
"""Check if there is a tilt series done when the series is ready."""
pylo.logginglib.log_debug(self.logger, ("Checking if the current " +
"series contains tilts."))
self.tilt_cache_values = {}
for d in self.tilt_directions:
self.tilt_cache_values[d] = {}
if isinstance(self.controller.measurement.steps, pylo.MeasurementSteps):
# measurement steps object contains a set of all used variables for
# direct access
iterator = self.controller.measurement.steps.series_variables
else:
# use a map in a normal list of dicts
iterator = map(lambda s: s["variable"],
self.controller.measurement.steps)
for d in self.tilt_directions:
self.tilt_cache_values[d]["type"] = self.controller.configuration.getValue(
self._getTiltConfigName(d), "correction-type", datatype=str,
default_value=None)
pylo.logginglib.log_info(self.logger, ("Tilt correction " +
"in '{}' direction " +
"is '{}'").format(d,
self.tilt_cache_values[d]["type"]))
if self.tilt_cache_values[d]["type"] == "Off":
continue
self.tilt_cache_values[d]["id"] = self.controller.configuration.getValue(
self._getTiltConfigName(d), "tilt-id", datatype=str,
default_value=None)
self.tilt_cache_values[d]["present-in-series"] = False
if self.tilt_cache_values[d]["id"] in iterator:
pylo.logginglib.log_info(self.logger, ("Found a tilt id '{}' in "+
"the measurement steps, " +
"tilt correction for '{}' " +
"tilt is available").format(
self.tilt_cache_values[d]["id"],
d))
self.tilt_cache_values[d]["present-in-series"] = True
if not self.tilt_cache_values[d]["present-in-series"]:
pylo.logginglib.log_debug(self.logger, ("Tilt id '{}' is not " +
"used in the current " +
"series. No tilt " +
"correction for the " +
"'{}' direction").format(
self.tilt_cache_values[d]["id"],
d))
def correctTilts(self, *args, **kwargs):
"""Realign the stage before every measurement step."""
for d in self.tilt_directions:
if (self.tilt_cache_values[d]["type"] != "Off" and
self.tilt_cache_values[d]["present-in-series"]):
try:
tilt = self.controller.microscope.getMeasurementVariableValue(
self.tilt_cache_values[d]["id"])
except ValueError:
continue
if ("last-value" not in self.tilt_cache_values[d] or
math.isclose(self.tilt_cache_values[d]["last-value"], tilt)):
self.tilt_cache_values[d]["last-value"] = tilt
pylo.logginglib.log_debug(self.logger, ("Skipping tilt " +
"correction in '{}' " +
"direction, the " +
"tilts did not " +
"change since " +
"the last step " +
"or this is the " +
"first step."))
continue
if "Automatic" in self.tilt_cache_values[d]["type"]:
for sd in ("x", "y"):
stage_key = "stage-{}".format(sd)
if not stage_key in self.tilt_cache_values[d]:
self.tilt_cache_values[d][stage_key] = self.controller.configuration.getValue(
self._getTiltConfigName(d),
"stage-{}-variable-id".format(sd), datatype=str,
default_value=None)
l_key = "l{}".format(sd)
if not l_key in self.tilt_cache_values[d]:
self.tilt_cache_values[d][l_key] = self.controller.configuration.getValue(
self._getTiltConfigName(d), "stage-{}".format(sd),
datatype=float, default_value=0)
if (isinstance(self.tilt_cache_values[d][l_key], (int, float)) and
not math.isclose(self.tilt_cache_values[d][l_key], 0, abs_tol=1e-6) and
self.tilt_cache_values[d][stage_key] is not None and
self.tilt_cache_values[d][stage_key] != ""):
stage_d = (self.tilt_cache_values[d][l_key] *
(math.cos(math.radians(self.tilt_cache_values[d]["last-value"])) -
math.cos(math.radians(tilt))))
pylo.logginglib.log_debug(self.logger,
("Calculating stage difference by " +
"d = {} * (cos(a) - cos(b)) with " +
"{}='{}', a='{}' and b='{}' => d='{}'").format(
l_key, l_key,
self.tilt_cache_values[d][l_key],
self.tilt_cache_values[d]["last-value"],
tilt, stage_d))
try:
stage_value = self.controller.microscope.getMeasurementVariableValue(
self.tilt_cache_values[d][stage_key])
except KeyError:
# stage variable is invalid, disable for future
# runs
self.tilt_cache_values[d][stage_key] = None
self.tilt_cache_values[d][l_key] = 0
continue
try:
self.controller.microscope.setMeasurementVariableValue(
self.tilt_cache_values[d][stage_key],
stage_value + stage_d)
pylo.logginglib.log_info(self.logger,
("Correcting '{}' tilt in '{}' direction, " +
"by moving stage by '{}' (target value " +
"is '{}').").format(d, sd, stage_d,
stage_value + stage_d))
except ValueError as e:
pylo.logginglib.log_error(e)
else:
pylo.logginglib.log_debug(self.logger,
("Skipping '{}' tilt correction in '{}' direction, " +
"the either the stage variable id '{}' or " +
"the stage correction factor '{}' is " +
"invalid.").format(d, sd,
self.tilt_cache_values[d][stage_key],
self.tilt_cache_values[d][l_key]))
if "Manual" in self.tilt_cache_values[d]["type"]:
self.controller.view.showHint("Pausing for tilt " +
"correction.\n\n" +
"Please move the stage " +
"to compensate translation "+
"caused by tilting. Press " +
"'Ok' if you want to " +
"continue.")
pylo.logginglib.log_debug(self.logger, ("Showing correction " +
"tilt dialog."))
self.tilt_cache_values[d]["last-value"] = tilt
|
import boto3
import botocore
import threading
from django.http import HttpResponse
from django.core import serializers
from django.core.exceptions import FieldDoesNotExist, ObjectDoesNotExist, PermissionDenied
from django.shortcuts import render
from django.contrib.auth.models import User
from api.models import Video, Device, RemoteHistory, Lock, Record, Door, AddDevice
from api.serializers import VideoSerializer, DeviceSerializer, RemoteHistorySerializer, RecordSerializer, LockSerializer, AddDeviceSerializer
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.request import Request
from rest_framework.response import Response
from rest_framework.authtoken.models import Token
from rest_framework.authentication import TokenAuthentication
from boto3.session import Session
from src.settings import AWS_REGION
from src.settings import S3_ACCESS_URL
from src.settings import S3_ACCESS_KEY_ID, S3_SECRET_ACCESS_KEY, S3_STORAGE_BUCKET_NAME
import time
from datetime import datetime, timedelta
import json
import uuid
# Create your views here.
#로그인 및 토큰 반환
class Login(APIView) :
def get(self, request, format = None) : # request query에 door_id 포함되어있음 : api/auth?door_id=12345
try :
request_id = request.GET.get('door_id', None)
if request_id == None :
raise FieldDoesNotExist
queryset = Door.objects.filter(door_id = request_id) # door_id 유효성 검색
if queryset.exists() :# 유효할 때
userid = uuid.uuid4()
pw = uuid.uuid4()
user = User.objects.create_user(username=str(userid), password=str(pw))
token = Token.objects.create(user=user)
res = {
'is_available' : True,
'access_token' : token.key
}
else :
res = {
'is_available' : False
}
return Response(res, status = status.HTTP_200_OK)
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
def post(self, request, format = None) :
Door.objects.create(door_id = 12345)
Lock.objects.create(id=1)
Record.objects.create(id=1)
AddDevice.objects.create(id=1)
return Response({
'msg' : 'doorid값 삽입 완료',
})
#기기 관련 api
class Devices(APIView) :
# 기기 목록 조회
def get(self, request, format = None) :
try :
queryset = Device.objects.all()
serializer = DeviceSerializer(queryset, many = True)
res = {
'deviceList': serializer.data
}
return Response(res, status = status.HTTP_200_OK)
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 기기 추가 요청
def put(self, request, format = None) :
try :
if request.auth == None :
raise PermissionDenied
print(request.body)
target = AddDevice.objects.get(id=1)
serializer = AddDeviceSerializer(target, many=False)
state = serializer.data['state']
if state == False:
print(">> 기기추가 요청이 들어옴")
target.state = True
target.save()
return Response({
'msg' : 'changed state successfully'
}, status = status.HTTP_200_OK)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 기기 추가
def post(self, request, format = None) : # request body에 rfid_id 포함되어있음
try :
print(request.data)
request_id = request.data.get('rfid_id', None)
if request_id == None :
raise FieldDoesNotExist
queryset = Device.objects.create(rfid_id = request_id)
queryset.save()
select = Device.objects.filter(rfid_id = request_id).values()
device_id = select[0]['device_id']
rfid_id = select[0]['rfid_id']
created = select[0]['created']
return Response({
"device_id" : device_id,
"rfid_id" : rfid_id,
"created" : created
}, status = status.HTTP_200_OK)
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 기기 삭제
def delete(self, request, device_id, format = None): # request URI에 device_id(자동생성되는 기기 고유 번호 != rfid_id) 포함
try :
if request.auth == None :
raise PermissionDenied
request_id = device_id
if request_id == None:
raise FieldDoesNotExist
queryset = Device.objects.get(device_id=request_id)
queryset.delete()
return Response({
'msg' : 'success delete device'
})
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 원격 잠금 해제
class Remote(APIView):
# 원격 잠금 해제 기록 조회
def get(self, request, format = None) :
#models.py의 class History 사용.
try:
if request.auth == None :
raise PermissionDenied
queryset = RemoteHistory.objects.all()
serializer = RemoteHistorySerializer(queryset, many = True)
res = {
"remoteHistoryList": serializer.data
}
return Response(res, status = status.HTTP_200_OK)
except PermissionDenied as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 원격 잠금 해제
def post(self, request, format = None) :
try:
if request.auth == None :
raise PermissionDenied
print(request.body)
data = json.loads(request.body)
device_name = data.get('device_name', None)
if device_name == None :
raise FieldDoesNotExist
else:
target = Lock.objects.get(id=1)
serializer = LockSerializer(target, many=False)
state = serializer.data['state']
if state == True:
print(">> 원격 잠금해제 요청이 들어옴")
# 기록에 저장
now = datetime.now()
queryset = RemoteHistory.objects.create(device_name=device_name, created=now)
queryset.save()
# 잠금 해제 상태로 변경
target.state = False
target.save()
return Response({
'msg' : 'success remote unlock'
}, status = status.HTTP_200_OK)
except FieldDoesNotExist as error:
return Response({
'error': "FieldDoesNotExist ",
'date': datetime.now()
}, status=status.HTTP_400_BAD_REQUEST)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 비디오 목록 조회
class VideoList(APIView) :
def get(self, request, format = None) :
try :
if request.auth == None :
raise PermissionDenied
queryset = Video.objects.all()
serializer = VideoSerializer(queryset, many = True)
res = {
'videoList': serializer.data
} # 응답코드에 포함될 데이터
return Response(res, status = status.HTTP_200_OK)
except FieldDoesNotExist as error:
return Response({
'error': "FieldDoesNotExist ",
'date': datetime.now()
}, status=status.HTTP_400_BAD_REQUEST)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 비디오 확인
class VideoDetail(APIView) :
def get(self, request, vid_name, format = None) : # 요청한 URI에 vid_name가 포함되어있음
try :
if request.auth == None :
raise PermissionDenied
request_id = vid_name
if request_id == 'None' :
raise FieldDoesNotExist
queryset = Video.objects.filter(vid_name = request_id) # door_id 유효성 검색
if not queryset.exists():
raise FieldDoesNotExist
download_url = S3_ACCESS_URL + str(request_id) + '.mp4' # S3 다운로드 링크 변환
if not download_url :
raise ObjectDoesNotExist
res = {
's3link' : download_url
} # 응답 코드에 보낼 데이터
return Response(res, status = status.HTTP_200_OK)
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
except ObjectDoesNotExist as error :
return Response({
'error' : "ObjectDoesNotExist",
'date' : datetime.now()
}, status = status.HTTP_404_NOT_FOUND)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 비디오 수동 삭제
def delete(self, request, vid_name, format = None) : # request URI에 vid_name가 포함되어있음 : api/video/{vid_name}
try :
if request.auth == None :
raise PermissionDenied
request_id = vid_name
if request_id == 'None' :
raise FieldDoesNotExist
session = boto3.session.Session(aws_access_key_id = S3_ACCESS_KEY_ID, aws_secret_access_key = S3_SECRET_ACCESS_KEY, region_name = AWS_REGION)
s3 = session.client('s3')
target = Video.objects.get(vid_name = request_id)
s3.delete_object(Bucket = S3_STORAGE_BUCKET_NAME, Key = str(target.vid_name) + '.mp4')
s3.delete_object(Bucket = S3_STORAGE_BUCKET_NAME, Key = str(target.vid_name) + '_thumb.jpg')
target.delete()
return Response(status = status.HTTP_200_OK)
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
# 비디오 자동 삭제
class CheckDate(APIView) :
def delete(self, request, format = None) :
checkdate = datetime.now() + timedelta(days = -7)
quaryset = Video.objects.filter(created__lt = checkdate)
session = boto3.session.Session(aws_access_key_id = S3_ACCESS_KEY_ID, aws_secret_access_key = S3_SECRET_ACCESS_KEY, region_name = AWS_REGION)
s3 = session.client('s3')
for delvid in quaryset :
s3.delete_object(Bucket = S3_STORAGE_BUCKET_NAME, Key = str(delvid.vid_name) + '.mp4')
quaryset.delete()
return Response(status = status.HTTP_200_OK)
# 비디오 녹화 설정 조회/변경
class Recording(APIView) :
def get(self, request, format = None) :
try :
if request.auth == None :
raise PermissionDenied
target = Record.objects.get(id = 1)
serializer = RecordSerializer(target, many = False)
res = {
'recording' : serializer.data['recording']
}
return Response(res, status = status.HTTP_200_OK)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
def put(self, request, format = None) :
try :
if request.auth == None :
raise PermissionDenied
print(request.body)
data = json.loads(request.body)
if 'recording' not in data:
raise FieldDoesNotExist
target = Record.objects.filter(id = 1)
target.update(recording = data['recording'])
res = {
'recording' : data['recording']
}
return Response(res, status = status.HTTP_200_OK)
except PermissionDenied as error :
return Response({
'error' : "PermissionDenied ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
except FieldDoesNotExist as error :
return Response({
'error' : "FieldDoesNotExist ",
'date' : datetime.now()
}, status = status.HTTP_400_BAD_REQUEST)
|
# Copyright (c) 2017-2023 Digital Asset (Switzerland) GmbH and/or its affiliates. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from datetime import datetime
from logging import Logger
from os import PathLike
import sys
from typing import (
AbstractSet,
Any,
AsyncIterator,
Awaitable,
Callable,
Collection,
Iterator,
Literal,
Optional,
Protocol,
Sequence,
TypeVar,
Union,
overload,
runtime_checkable,
)
from ..damlast import TypeConName
from ..damlast.daml_lf_1 import PackageRef
from ..damlast.lookup import SymbolLookup
from ..prim import ContractData, ContractId, Party, TimeDeltaLike
from ..query import Queries, Query
from .aio import Connection as AioConnection, QueryStream as AioQueryStream
from .api_types import (
ActAs,
Admin,
ArchiveEvent,
Boundary,
Command,
CommandMeta,
CreateAndExerciseCommand,
CreateCommand,
CreateEvent,
Event,
EventOrBoundary,
ExerciseByKeyCommand,
ExerciseCommand,
ExerciseResponse,
MeteringReport,
PartyInfo,
ReadAs,
Right,
SubmitResponse,
User,
Version,
)
from .blocking import Connection as BlockingConnection, QueryStream as BlockingQueryStream
from .config import Config
__all__ = [
"aio",
"ActAs",
"Admin",
"ArchiveEvent",
"Boundary",
"Command",
"CommandMeta",
"CreateAndExerciseCommand",
"CreateCommand",
"CreateEvent",
"Event",
"EventOrBoundary",
"ExerciseByKeyCommand",
"ExerciseCommand",
"ExerciseResponse",
"PartyInfo",
"PackageService",
"MeteringReport",
"ReadAs",
"Connection",
"QueryStream",
"User",
]
CreateFn = TypeVar("CreateFn", bound=Callable[[CreateEvent], SubmitResponse])
ArchiveFn = TypeVar("ArchiveFn", bound=Callable[[ArchiveEvent], SubmitResponse])
BoundaryFn = TypeVar("BoundaryFn", bound=Callable[[Boundary], SubmitResponse])
# These are written as Protocols with __call__ instead of a Callable so that they can be safely
# overloaded for the asynchronous variants. See dazl.ledger.aio's typing file.
class OnCreateDecorator(Protocol):
def __call__(self, __fn: CreateFn) -> CreateFn: ...
class OnArchiveDecorator(Protocol):
def __call__(self, __fn: ArchiveFn) -> ArchiveFn: ...
class OnBoundaryDecorator(Protocol):
def __call__(self, __fn: BoundaryFn) -> BoundaryFn: ...
# These overload declarations were painfully constructed in careful consultation with:
# https://github.com/python/mypy/issues/6580
#
# * ``blocking: Literal[False] = False`` must appear as the very first argument to the first
# overload; this reflects the _actual_ default value combined with a literal value marker.
# Putting this parameter in any other position causes the mypy error "Overloaded function
# signatures 1 and 2 overlap with incompatible return types".
# * All other subsequent overloads must define the ``blocking`` parameter as a _non-optional_
# positional parameter. Specifying a default value in these cases confuses mypy and MUST be
# avoided.
# * An explicit overload typed as a bool is also required.
#
# Separately PyCharm thinks the name of the parameter "blocking" conflicts with the import to
# dazl.ledger.blocking above, even though that's not actually the case. Either way we silence
# that warning too.
#
# TODO: Look into ways of generating this signatures from Config.create
#
# noinspection PyShadowingNames
@overload
def connect(
*,
url: Optional[str] = None,
host: Optional[str] = None,
port: Optional[int] = None,
scheme: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
admin: Optional[bool] = False,
ledger_id: Optional[str] = None,
application_name: Optional[str] = None,
oauth_token: Optional[str] = None,
oauth_token_file: Optional[str] = None,
ca: Optional[bytes] = None,
ca_file: Optional[PathLike] = None,
cert: Optional[bytes] = None,
cert_file: Optional[PathLike] = None,
cert_key: Optional[bytes] = None,
cert_key_file: Optional[PathLike] = None,
connect_timeout: Optional[TimeDeltaLike] = None,
use_http_proxy: bool = True,
logger: Optional[Logger] = None,
logger_name: Optional[str] = None,
log_level: Optional[str] = None,
lookup: Optional[SymbolLookup] = None,
) -> AioConnection: ...
# noinspection PyShadowingNames
@overload
def connect(
*,
blocking: Literal[False],
url: Optional[str] = None,
host: Optional[str] = None,
port: Optional[int] = None,
scheme: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
admin: Optional[bool] = False,
ledger_id: Optional[str] = None,
application_name: Optional[str] = None,
oauth_token: Optional[str] = None,
oauth_token_file: Optional[str] = None,
ca: Optional[bytes] = None,
ca_file: Optional[PathLike] = None,
cert: Optional[bytes] = None,
cert_file: Optional[PathLike] = None,
cert_key: Optional[bytes] = None,
cert_key_file: Optional[PathLike] = None,
connect_timeout: Optional[TimeDeltaLike] = None,
use_http_proxy: bool = True,
logger: Optional[Logger] = None,
logger_name: Optional[str] = None,
log_level: Optional[str] = None,
lookup: Optional[SymbolLookup] = None,
) -> AioConnection: ...
# noinspection PyShadowingNames
@overload
def connect(
*,
blocking: Literal[True],
url: Optional[str] = None,
host: Optional[str] = None,
port: Optional[int] = None,
scheme: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
admin: Optional[bool] = False,
ledger_id: Optional[str] = None,
application_name: Optional[str] = None,
oauth_token: Optional[str] = None,
oauth_token_file: Optional[str] = None,
ca: Optional[bytes] = None,
ca_file: Optional[PathLike] = None,
cert: Optional[bytes] = None,
cert_file: Optional[PathLike] = None,
cert_key: Optional[bytes] = None,
cert_key_file: Optional[PathLike] = None,
connect_timeout: Optional[TimeDeltaLike] = None,
use_http_proxy: bool = True,
logger: Optional[Logger] = None,
logger_name: Optional[str] = None,
log_level: Optional[str] = None,
lookup: Optional[SymbolLookup] = None,
) -> BlockingConnection: ...
# noinspection PyShadowingNames
@overload
def connect(
*,
blocking: bool,
url: Optional[str] = None,
host: Optional[str] = None,
port: Optional[int] = None,
scheme: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
admin: Optional[bool] = False,
ledger_id: Optional[str] = None,
application_name: Optional[str] = None,
oauth_token: Optional[str] = None,
oauth_token_file: Optional[str] = None,
ca: Optional[bytes] = None,
ca_file: Optional[PathLike] = None,
cert: Optional[bytes] = None,
cert_file: Optional[PathLike] = None,
cert_key: Optional[bytes] = None,
cert_key_file: Optional[PathLike] = None,
connect_timeout: Optional[TimeDeltaLike] = None,
use_http_proxy: bool = True,
logger: Optional[Logger] = None,
logger_name: Optional[str] = None,
log_level: Optional[str] = None,
lookup: Optional[SymbolLookup] = None,
) -> Connection: ...
class PackageService(Protocol):
def get_package(
self, package_id: PackageRef, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[bytes, Awaitable[bytes]]: ...
def list_package_ids(
self, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[AbstractSet[PackageRef], Awaitable[AbstractSet[PackageRef]]]: ...
@runtime_checkable
class Connection(PackageService, Protocol):
@property
def config(self) -> Config: ...
@property
def codec(self) -> Any: ...
@property
def is_closed(self) -> bool: ...
def open(self) -> Union[None, Awaitable[None]]: ...
def close(self) -> Union[None, Awaitable[None]]: ...
def create(
self,
__template_id: Union[str, TypeConName],
__payload: ContractData,
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[CreateEvent, Awaitable[CreateEvent]]: ...
def create_and_exercise(
self,
__template_id: Union[str, TypeConName],
__payload: ContractData,
__choice_name: str,
__argument: Optional[ContractData] = None,
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[ExerciseResponse, Awaitable[ExerciseResponse]]: ...
def exercise(
self,
__contract_id: ContractId,
__choice_name: str,
__argument: Optional[ContractData] = None,
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[ExerciseResponse, Awaitable[ExerciseResponse]]: ...
def exercise_by_key(
self,
__template_id: Union[str, TypeConName],
__choice_name: str,
__key: Any,
__argument: Optional[ContractData] = None,
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[ExerciseResponse, Awaitable[ExerciseResponse]]: ...
def submit(
self,
__commands: Union[Command, Sequence[Command]],
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[None, Awaitable[None]]: ...
def get_ledger_end(
self, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[str, Awaitable[str]]: ...
def archive(
self,
__contract_id: ContractId,
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[ArchiveEvent, Awaitable[ArchiveEvent]]: ...
def archive_by_key(
self,
__template_id: str,
__key: Any,
*,
workflow_id: Optional[str] = None,
command_id: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
act_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[ArchiveEvent, Awaitable[ArchiveEvent]]: ...
def query(
self,
__template_id: Union[str, TypeConName] = "*",
__query: Query = None,
*,
read_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> QueryStream: ...
def query_many(
self,
*queries: Queries,
read_as: Union[None, Party, Collection[Party]],
timeout: Optional[TimeDeltaLike] = ...,
) -> QueryStream: ...
def stream(
self,
__template_id: Union[str, TypeConName] = "*",
__query: Query = None,
*,
offset: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> QueryStream: ...
def stream_many(
self,
*queries: Queries,
offset: Optional[str] = None,
read_as: Union[None, Party, Collection[Party]] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> QueryStream: ...
def get_user(
self, user_id: Optional[str] = None, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[User, Awaitable[User]]: ...
def create_user(
self,
user: User,
rights: Optional[Sequence[Right]] = ...,
*,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[User, Awaitable[User]]: ...
def list_users(
self, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[Sequence[User], Awaitable[Sequence[User]]]: ...
def list_user_rights(
self, user_id: Optional[str] = None, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[Sequence[Right], Awaitable[Sequence[Right]]]: ...
def allocate_party(
self,
*,
identifier_hint: Optional[str] = None,
display_name: Optional[str] = None,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[PartyInfo, Awaitable[PartyInfo]]: ...
def list_known_parties(
self, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[Sequence[PartyInfo], Awaitable[Sequence[PartyInfo]]]: ...
def upload_package(
self, __contents: bytes, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[None, Awaitable[None]]: ...
def get_version(
self, *, timeout: Optional[TimeDeltaLike] = ...
) -> Union[Version, Awaitable[Version]]: ...
def get_metering_report(
self,
from_: datetime,
to: Optional[datetime] = None,
application_id: Optional[str] = None,
*,
timeout: Optional[TimeDeltaLike] = ...,
) -> Union[MeteringReport, Awaitable[MeteringReport]]: ...
@runtime_checkable
class QueryStream(Protocol):
@overload
def on_create(self) -> OnCreateDecorator: ...
@overload
def on_create(self, __fn: CreateFn) -> CreateFn: ...
@overload
def on_create(self, __name: Union[str, TypeConName]) -> OnCreateDecorator: ...
@overload
def on_create(self, __name: Union[str, TypeConName], __fn: CreateFn) -> CreateFn: ...
@overload
def on_archive(self) -> OnArchiveDecorator: ...
@overload
def on_archive(self, __fn: ArchiveFn) -> ArchiveFn: ...
@overload
def on_archive(self, __name: Union[str, TypeConName]) -> OnArchiveDecorator: ...
@overload
def on_archive(self, __name: Union[str, TypeConName], __fn: ArchiveFn) -> ArchiveFn: ...
@overload
def on_boundary(self) -> OnBoundaryDecorator: ...
@overload
def on_boundary(self, __fn: BoundaryFn) -> BoundaryFn: ...
def close(self) -> Union[None, Awaitable[None]]: ...
def run(self) -> Union[None, Awaitable[None]]: ...
def creates(self) -> Union[Iterator[CreateEvent], AsyncIterator[CreateEvent]]: ...
def events(self) -> Union[Iterator[Event], AsyncIterator[Event]]: ...
def items(self) -> Union[Iterator[EventOrBoundary], AsyncIterator[EventOrBoundary]]: ...
|
#Claire Yegian and Lea Adams-Blackmore
#4/30/18
#strategy5.py - finds exact value for S and D and creates simulation for strategy 5 (pay S above D)
from random import randint
#Exact value
N = int(input('Enter the number of marbles: '))
W = int(input('Enter the monetary prize: '))
marbleList = []
runs = 0
while runs <= N:
marbleList.append([runs, N - runs])
runs += 1
sumProb = 0
for item in marbleList:
red = item[0]
green = item[1]
if red >= 3 and green >= 3:
sumProb += (((red/N)*((red-1)/(N-1))*((red-2)/(N-2))) + ((green/N)*((green-1)/(N-1))*((green-2)/(N-2))) + ((red/N)*((green)/(N-1))*((red-1)/(N-2))*((red-2)/(N-3))) + ((red/N)*((green)/(N-1))*((green-1)/(N-2))*((green-2)/(N-3))) + ((green/N)*(red/(N-1))*((green-1)/(N-2))*((green-2)/(N-3))) + ((green/N)*(red/(N-1))*((red-1)/(N-2))*((red-2)/(N-3))))
elif red < 3 and red >= 1:
sumProb += (((green/N)*((green-1)/(N-1))*((green-2)/(N-2))) + ((red/N)*((green)/(N-1))*((green-1)/(N-2))*((green-2)/(N-3))) + ((green/N)*(red/(N-1))*((green-1)/(N-2))*((green-2)/(N-3))))
elif red <1:
sumProb += ((green/N)*((green-1)/(N-1))*((green-2)/(N-2)))
elif green < 3 and green >= 1:
sumProb += (((red/N)*((red-1)/(N-1))*((red-2)/(N-2))) + ((red/N)*((green)/(N-1))*((red-1)/(N-2))*((red-2)/(N-3))) + ((green/N)*(red/(N-1))*((red-1)/(N-2))*((red-2)/(N-3))))
elif red <1:
sumProb += ((red/N)*((red-1)/(N-1))*((red-2)/(N-2)))
S = (sumProb/N)*W - (W/2)
D = (W/2)
print(' ')
print('Theoretical: ')
print('You will pay',(sumProb/N)*W - (W/2),'dollars extra.')
print('S equals $',S,', and D equals $',D, 'The total cost is $', (S + D), 'or', ((S + D)/W)*100, 'percent of the total monetary prize')
#Simulation
w5ins = 0
r5uns = 0
while r5uns <= 1000:
r5ed = randint(0,N)
g5reen = N - r5ed
m5arbleList = []
i1tem = 0
while i1tem < g5reen:
m5arbleList.append(2)
i1tem += 1
i2tem = 0
while i2tem < r5ed:
m5arbleList.append(1)
i2tem += 1
g1uess = m5arbleList[randint(0,2)]
g2uess = m5arbleList[randint(6,9)]
if g1uess == g2uess:
f5inalGuess = g1uess
elif g1uess != g2uess:
f5inalGuess = m5arbleList[randint(3,5)]
m5arblePicked = m5arbleList[randint(0,N-1)]
if f5inalGuess == m5arblePicked:
w5ins += 1
r5uns += 1
print(' ')
print('Simulation: ')
print('You won',w5ins,'times out of 1000 or',w5ins/10,'percent of the time.')
|
import netCDF3, glob, numpy
for file in glob.glob("*.nc"):
nc = netCDF3.Dataset(file, 'r')
print file, numpy.sum( nc.variables['pr'][:] )
nc.close()
|
import torch
import numpy
if __name__ == '__main__':
x = torch.tensor([
[1., 2., 3.],
[4., 5., 6.]
])
print('x:')
print(x)
print('------------------------------------------------')
# x.data
print('x.data:')
print(x.data)
print('------------------------------------------------')
# x.grad
print('x.grad:')
print(x.grad)
print('------------------------------------------------')
# tensor和ndarray互转
x_numpy = x.numpy()
print(type(x_numpy))
x_tensor = torch.from_numpy(x_numpy)
print(type(x_tensor))
print('------------------------------------------------')
# torch tensor 和 numpy ndarray共享内存
x_numpy = x.numpy()
print('x:')
print(x)
print('x_numpy:', )
print(x_numpy)
x[0, 0] = 100.0
print('x:')
print(x)
print('x_numpy:', )
print(x_numpy)
print('------------------------------------------------')
print(torch.cuda.is_available())
print('------------------------------------------------')
pass
|
from SPARQLWrapper import SPARQLWrapper, XML, JSON
sparql = SPARQLWrapper("")
queryString = ""
sparql.setQuery(queryString)
sparql.setReturnFormat(JSON) # OR XML, OR RDF etc.
# return the spqarl object containing bound results
results = sparql.query().convert()
for result in results:
print(result)
|
# -*- coding: utf-8 -*-
"""Configuration.
This module contains flags to turn on and off optional modules.
"""
from importlib import util
cupy_enabled = util.find_spec("cupy") is not None
if cupy_enabled: # pragma: no cover
cudnn_enabled = util.find_spec("cupy.cuda.cudnn") is not None
nccl_enabled = util.find_spec("cupy.cuda.nccl") is not None
else:
cudnn_enabled = False
nccl_enabled = False
mpi4py_enabled = util.find_spec("mpi4py") is not None
pytorch_enabled = util.find_spec("torch") is not None
|
import mxnet as mx
import cv2
import numpy as np
from os.path import join
import os
from logger import logger
os.environ["MXNET_CPU_WORKER_NTHREADS"] = "4"
def eval_res(class_id,num_id,eval_epoch,root_dir = '/home/lhw/face/faceRec'):
print(class_id,num_id,eval_epoch)
batch_size = 512
val_label = None
imgs = None
attr_len = [int(num_id)]
mu = 2
width = 110 * mu
longth = int(160/8*7 * mu)
longth_ = int(longth/8*6)
width_ = int(width /8*6)
folder_name = '{}_data_{}/'.format(class_id,num_id)
class_num_id = '{}_data_{}/'.format(class_id,num_id)
resnet_version = '152'
checkpoint_name ='fine-tuned-resnet{}-{}-{}'.format(resnet_version,class_id,num_id)
pretrain_model_name = 'resnet-{}'.format(resnet_version)
def ge_val_label(folder_name):
val_label = None
augs = mx.image.CreateAugmenter(data_shape=(3,longth_, width_),rand_crop=True,rand_resize=False, rand_mirror=True, brightness=0.125, contrast=0.125, rand_gray=0.05,saturation=0.125, pca_noise=0, inter_method=10)
val_iter= mx.image.ImageIter(batch_size=1, data_shape=(3, longth_, width_), label_width=1,
path_imgidx='cloth_val.idx', path_imgrec='cloth_val.rec', shuffle=False,
aug_list=augs)
for batch in val_iter:
l = batch.label[0]
if val_label is None:
val_label = l
else:
val_label = mx.ndarray.concat(val_label,l,dim=0)
#print(mx.ndarray.concat(l,l,dim=1))
val_label = val_label.as_in_context(mx.cpu())
print(val_label.shape)
return val_label
def eval_avage(fea_list,val_label):
res_final = mx.nd.zeros(fea_list[0].shape,ctx=mx.gpu())
val_label = val_label.as_in_context(mx.gpu())
#res_final = final_res[0]
for i in fea_list:
res_final += i
res_final/= len(fea_list)
acc = mx.metric.Accuracy()
top2 = mx.metric.TopKAccuracy(top_k=2)
acc.update(labels=[val_label],preds=[res_final])
top2.update(labels=[val_label],preds=[res_final])
logger.info(acc.get())
logger.info(top2.get())
return res_final
os.chdir(join(root_dir,folder_name))
def do_multi_predict(model_name,batch_size=512,folder_name=folder_name,epoch_num=eval_epoch,tt=1):
#sym, arg_params, aux_params = mx.model.load_checkpoint('fine-tuned-firstclass-res18-use-resize', 25)
sym, arg_params, aux_params = mx.model.load_checkpoint(model_name,epoch_num)
mod = mx.mod.Module(symbol=sym, context=mx.gpu(), label_names=None)
mod.bind(for_training=False, data_shapes=[('data', (batch_size,3,longth_,width_))],
label_shapes=mod._label_shapes)
mod.set_params(arg_params, aux_params, allow_missing=True)
augs = [mx.image.CenterCropAug(size=(width,longth)),mx.image.ForceResizeAug((width_,longth_))]
#augs += mx.image.CreateAugmenter(data_shape=(3,longth_, width_),rand_crop=False,rand_resize=False, rand_mirror=True, brightness=0.125, contrast=0.125, rand_gray=0.05,saturation=0.125, pca_noise=0, inter_method=10)
final_res = None
print(model_name,epoch_num)
# define a simple data batch
for i in range(tt):
print(i)
val_iter= mx.image.ImageIter(batch_size=batch_size, data_shape=(3, longth_, width_), label_width=1,
path_imgidx='cloth_val.idx', path_imgrec='cloth_val.rec', shuffle=False,
aug_list=augs)
res = mod.predict(val_iter,always_output_list=True)
if final_res is None:
final_res = res
else:
final_res += res
del mod
return final_res
fea_list = do_multi_predict(checkpoint_name,tt=5,epoch_num=eval_epoch)
#res_final = final_res[0]
'''
res_final = mx.nd.zeros(fea_list[0].shape,ctx=mx.cpu())
for i in fea_list:
res_final += i
res_final/= len(fea_list)
'''
#print(1,10,3,4,5,6,7,8)
#rrrr = ['帽子','鞋子','披带类','上装','裤子','裙子','连体装','包包']
#print(res_final,rrrr[res_final[0].asnumpy().argmax()])
val_label= ge_val_label(folder_name=folder_name)
res_final= eval_avage(fea_list[0:5],val_label)
p = res_final.asnumpy()
l = val_label.asnumpy()
pred = []
ff = []
tt = []
fff = []
ttf = []
ttc = []
allf = []
the = 0.90
for i in range(len(p)):
pp = p[i]
mm = pp.argmax()
if mm != l[i]:
allf.append(pp[mm])
if mm != l[i] and pp[mm] <the:
ff.append(pp[mm])
else:
if pp[mm] < the:
tt.append(pp[mm])
ttc.append(mm)
#logger.info(len(tt),len(ff),len(ttf),len(fff),len(allf))
logger.info((len(tt)+len(ff))/res_final.shape[0])
logger.info((len(allf)-len(ff))/res_final.shape[0])
preds = res_final.asnumpy()
preds = preds.argmax(axis=1)
preds.shape
from sklearn.metrics import confusion_matrix,classification_report,f1_score,recall_score,accuracy_score
cm = confusion_matrix(l,preds)
cm = (cm/cm.sum(axis=1)[:,np.newaxis])
from pprint import pprint
logger.info(cm)
print(cm)
#print(len([i for i in ttc if i==])/500)
eval_res(10001,3,10,'/root/cloth')
#eval_res(23,7,10,'/root/cloth')
|
import numpy as np
import imageio
import Poisson as poi
import matplotlib.pyplot as plt
from scipy import ndimage
iter = 20
img = imageio.imread('../hdr-bilder/Bonita/Bonita_00512.png')
print(img.shape)
mosaic = np.zeros(img.shape[:2])
mosaic[::2, ::2] = img[::2, ::2, 0]
mosaic[1::2, ::2] = img[1::2, ::2, 1]
mosaic[::2, 1::2] = img[::2, 1::2, 1]
mosaic[1::2, 1::2] = img[1::2, 1::2, 2]
reconstructed = np.zeros(img.shape)
reconstructed[::2 ,::2, 0] = mosaic[::2, ::2]
reconstructed[1::2, ::2, 1] = mosaic[1::2, ::2]
reconstructed[::2, 1::2, 1] = mosaic[::2, 1::2]
reconstructed[1::2, 1::2, 2] = mosaic[1::2, 1::2]
mask = np.zeros((img.shape[0], img.shape[1]), dtype=bool)
mask[reconstructed[:, :, 0] == 0] = True
red_channel = poi.poisson(reconstructed[:, :, 0], iter, mask=mask, rand='neuman')
mask = np.zeros((img.shape[0], img.shape[1]), dtype=bool)
mask[reconstructed[:, :, 1] == 0] = True
green_channel = poi.poisson(reconstructed[:, :, 1], iter, mask=mask, rand='neuman')
mask = np.zeros((img.shape[0], img.shape[1]), dtype=bool)
mask[reconstructed[:, :, 2] == 0] = True
blue_channel = poi.poisson(reconstructed[:, :, 2], iter, mask=mask, rand='neuman')
rec_img = np.zeros(img.shape)
rec_img[:, :, 0] = red_channel[:, :, -1]
rec_img[:, :, 1] = green_channel[:, :, -1]
rec_img[:, :, 2] = blue_channel[:, :, -1]
rec_img = rec_img.astype(np.uint8)
plt.imshow(rec_img)
plt.show()
|
import csv
import pdb
from sklearn.metrics import accuracy_score, precision_score, recall_score, classification_report, confusion_matrix
import numpy as np
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
class Logger(object):
def __init__(self, path, header):
self.log_file = open(path, 'w')
self.logger = csv.writer(self.log_file, delimiter='\t')
self.logger.writerow(header)
self.header = header
def __del(self):
self.log_file.close()
def log(self, values):
write_values = []
for col in self.header:
assert col in values
write_values.append(values[col])
self.logger.writerow(write_values)
self.log_file.flush()
class Queue:
#Constructor creates a list
def __init__(self, max_size, n_classes):
self.queue = list(np.zeros((max_size, n_classes),dtype = float).tolist())
self.max_size = max_size
self.median = None
self.ma = None
self.ewma = None
#Adding elements to queue
def enqueue(self,data):
self.queue.insert(0,data)
self.median = self._median()
self.ma = self._ma()
self.ewma = self._ewma()
return True
#Removing the last element from the queue
def dequeue(self):
if len(self.queue)>0:
return self.queue.pop()
return ("Queue Empty!")
#Getting the size of the queue
def size(self):
return len(self.queue)
#printing the elements of the queue
def printQueue(self):
return self.queue
#Average
def _ma(self):
return np.array(self.queue[:self.max_size]).mean(axis = 0)
#Median
def _median(self):
return np.median(np.array(self.queue[:self.max_size]), axis = 0)
#Exponential average
def _ewma(self):
weights = np.exp(np.linspace(-1., 0., self.max_size))
weights /= weights.sum()
average = weights.reshape(1,self.max_size).dot( np.array(self.queue[:self.max_size]))
return average.reshape(average.shape[1],)
# def LevenshteinDistance(a,b):
# # This is a straightforward implementation of a well-known algorithm, and thus
# # probably shouldn't be covered by copyright to begin with. But in case it is,
# # the author (Magnus Lie Hetland) has, to the extent possible under law,
# # dedicated all copyright and related and neighboring rights to this software
# # to the public domain worldwide, by distributing it under the CC0 license,
# # version 1.0. This software is distributed without any warranty. For more
# # information, see <http://creativecommons.org/publicdomain/zero/1.0>
# "Calculates the Levenshtein distance between a and b."
# n, m = len(a), len(b)
# if n > m:
# # Make sure n <= m, to use O(min(n,m)) space
# a,b = b,a
# n,m = m,n
# current = range(n+1)
# for i in range(1,m+1):
# previous, current = current, [i]+[0]*n
# for j in range(1,n+1):
# add, delete = previous[j]+1, current[j-1]+1
# change = previous[j-1]
# if a[j-1] != b[i-1]:
# change = change + 1
# current[j] = min(add, delete, change)
# return current[n]
def load_value_file(file_path):
with open(file_path, 'r') as input_file:
value = float(input_file.read().rstrip('\n\r'))
return value
def calculate_accuracy(outputs, targets):
batch_size = targets.size(0)
_, pred = outputs.topk(1, 1, True)
pred = pred.t()
correct = pred.eq(targets.view(1, -1))
n_correct_elems = correct.float().sum().item()
return n_correct_elems / batch_size
def calculate_precision(outputs, targets):
batch_size = targets.size(0)
_, pred = outputs.topk(1, 1, True)
pred = pred.t()
return precision_score(targets.cpu().view(-1), pred.cpu().view(-1), average = 'macro')
def calculate_recall(outputs, targets):
batch_size = targets.size(0)
_, pred = outputs.topk(1, 1, True)
pred = pred.t()
return recall_score(targets.cpu().view(-1), pred.cpu().view(-1), average = 'macro')
#############################################
######## For Levenshtein Accuracy calculation
def LevenshteinDistance(r, h):
edit_distance_matrix = editDistance(r=r, h=h)
step_list = getStepList(r=r, h=h, d=edit_distance_matrix)
min_distance = float(edit_distance_matrix[len(r)][len(h)])
num_del = float(np.sum([s == "d" for s in step_list]))
num_ins = float(np.sum([s == "i" for s in step_list]))
num_sub = float(np.sum([s == "s" for s in step_list]))
word_error_rate = round((min_distance / len(r) * 100), 4)
del_rate = round((num_del / len(r) * 100), 4)
ins_rate = round((num_ins / len(r) * 100), 4)
sub_rate = round((num_sub / len(r) * 100), 4)
# return {"wer": word_error_rate, "del": del_rate, "ins": ins_rate, "sub": sub_rate}
return min_distance, num_del, num_ins, num_sub
def editDistance(r, h):
"""
Original Code from https://github.com/zszyellow/WER-in-python/blob/master/wer.py
This function is to calculate the edit distance of reference sentence and the hypothesis sentence.
Main algorithm used is dynamic programming.
Attributes:
r -> the list of words produced by splitting reference sentence.
h -> the list of words produced by splitting hypothesis sentence.
"""
d = np.zeros((len(r) + 1) * (len(h) + 1), dtype=np.uint8).reshape(
(len(r) + 1, len(h) + 1)
)
for i in range(len(r) + 1):
for j in range(len(h) + 1):
if i == 0:
d[0][j] = j
elif j == 0:
d[i][0] = i
for i in range(1, len(r) + 1):
for j in range(1, len(h) + 1):
if r[i - 1] == h[j - 1]:
d[i][j] = d[i - 1][j - 1]
else:
substitute = d[i - 1][j - 1] + 1
insert = d[i][j - 1] + 1
delete = d[i - 1][j] + 1
d[i][j] = min(substitute, insert, delete)
return d
def getStepList(r, h, d):
"""
Original Code from https://github.com/zszyellow/WER-in-python/blob/master/wer.py
This function is to get the list of steps in the process of dynamic programming.
Attributes:
r -> the list of words produced by splitting reference sentence.
h -> the list of words produced by splitting hypothesis sentence.
d -> the matrix built when calulating the editting distance of h and r.
"""
x = len(r)
y = len(h)
max_len = 3 * (x + y)
list = []
while True:
if (x <= 0 and y <= 0) or (len(list) > max_len):
break
elif x >= 1 and y >= 1 and d[x][y] == d[x - 1][y - 1] and r[x - 1] == h[y - 1]:
list.append("e")
x = max(x - 1, 0)
y = max(y - 1, 0)
elif y >= 1 and d[x][y] == d[x][y - 1] + 1:
list.append("i")
x = max(x, 0)
y = max(y - 1, 0)
elif x >= 1 and y >= 1 and d[x][y] == d[x - 1][y - 1] + 1:
list.append("s")
x = max(x - 1, 0)
y = max(y - 1, 0)
else:
list.append("d")
x = max(x - 1, 0)
y = max(y, 0)
return list[::-1]
|
# Generated by Django 2.2.1 on 2019-05-19 00:09
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('posts', '0006_auto_20190519_0006'),
]
operations = [
migrations.AlterField(
model_name='post',
name='header_title',
field=models.CharField(help_text='Title that shows on page. Should typically match meta title.', max_length=100, unique=True),
),
migrations.AlterField(
model_name='post',
name='meta_description',
field=models.CharField(blank=True, help_text='Brief description that shows up in Google search. Approx. 160 characters.', max_length=250),
),
migrations.AlterField(
model_name='post',
name='modification_date',
field=models.DateTimeField(auto_now=True, help_text='Date the post was modified from original version.'),
),
]
|
from pyasn1.type.namedtype import NamedType, NamedTypes, OptionalNamedType, DefaultedNamedType
from pyasn1.type.namedval import NamedValues
from asn1PERser.classes.data.builtin import *
from asn1PERser.classes.types.type import AdditiveNamedTypes
from asn1PERser.classes.types.constraint import MIN, MAX, NoConstraint, ExtensionMarker, SequenceOfValueSize, \
ValueRange, SingleValue, ValueSize, ConstraintOr, ConstraintAnd
class MyEnum(EnumeratedType):
subtypeSpec = ExtensionMarker(True)
enumerationRoot = NamedValues(
('zero', 0),
('one', 1),
('two', 2),
('three', 3),
)
extensionAddition = NamedValues(
('four', 4),
('five', 5),
)
namedValues = enumerationRoot + extensionAddition
class ThirdSequence(SequenceOfType):
componentType = OctetStringType()
class MyChoice(ChoiceType):
subtypeSpec = ExtensionMarker(True)
rootComponent = AdditiveNamedTypes(
NamedType('c0', IntegerType()),
NamedType('c1', ThirdSequence()),
NamedType('c2', BooleanType()),
)
extensionAddition = AdditiveNamedTypes(
NamedType('c3', IntegerType()),
NamedType('c4', BooleanType()),
)
componentType = rootComponent + extensionAddition
class YetOtherSeq(SequenceType):
subtypeSpec = ExtensionMarker(True)
rootComponent = AdditiveNamedTypes(
NamedType('myEnum', MyEnum()),
NamedType('myChoice', MyChoice()),
)
extensionAddition = AdditiveNamedTypes(
NamedType('add3', OctetStringType()),
NamedType('add4', IntegerType()),
)
componentType = rootComponent + extensionAddition
class OtherSequence(SequenceType):
subtypeSpec = ExtensionMarker(True)
rootComponent = AdditiveNamedTypes(
NamedType('yetOtherSeq', YetOtherSeq()),
NamedType('myBool', BooleanType()),
)
extensionAddition = AdditiveNamedTypes(
NamedType('add2', BitStringType()),
)
componentType = rootComponent + extensionAddition
class MySeq(SequenceType):
subtypeSpec = ExtensionMarker(True)
rootComponent = AdditiveNamedTypes(
NamedType('int0', IntegerType()),
NamedType('otherSeq', OtherSequence()),
)
extensionAddition = AdditiveNamedTypes(
NamedType('add0', IntegerType()),
NamedType('add1', BooleanType()),
)
componentType = rootComponent + extensionAddition
|
# coding: utf-8
"""Utility functions for MDN parsing."""
from __future__ import unicode_literals
from django.utils.six import text_type
import string
def date_to_iso(date):
"""Convert a datetime.Date to the ISO 8601 format, or None."""
if date:
return date.isoformat()
else:
return None
def end_of_line(text, pos):
"""Get the position of the end of the line from pos."""
try:
return text.index('\n', pos)
except ValueError:
return len(text)
def format_version(version):
"""Format a version to 1.0, 1.0.1, etc."""
if '.' in version:
return version
else:
assert version
assert int(version)
return version + '.0'
def is_new_id(_id):
"""Detect if an ID signifies a new resource.
New resource IDs are text strings prefixed with an underscore.
"""
return isinstance(_id, text_type) and _id[0] == '_'
def join_content(content_bits):
"""Construct a string with just the right whitespace."""
out = ''
nospace_before = '!,.;?[ '
nospace_after = ' '
for bit in content_bits:
if bit:
if (out and out[-1] not in nospace_after and
bit[0] not in nospace_before):
out += ' '
out += bit
return out
def normalize_name(name):
"""Normalize a name for IDs, slugs."""
to_remove = ('<code>', '</code>', '<', '>')
normalized_name = name.lower()
for removal in to_remove:
normalized_name = normalized_name.replace(removal, '')
return normalized_name
def slugify(word, length=50, suffix=''):
"""Create a slugged version of a word or phrase."""
raw = word.lower()
out = []
acceptable = string.ascii_lowercase + string.digits + '_-'
for c in raw:
if c in acceptable:
out.append(c)
else:
out.append('_')
slugged = ''.join(out)
while '__' in slugged:
slugged = slugged.replace('__', '_')
if slugged.endswith('_') and len(slugged) > 1:
slugged = slugged[:-1]
suffix = text_type(suffix) if suffix else ''
with_suffix = slugged[slice(length - len(suffix))] + suffix
return with_suffix
|
# '''
# \d 可以匹配一个数字
# \w 可以匹配一个字母
# . 可以匹配任何字符
# * 表示任意个字符
# + 表示至少一个字符
# ？ 表示1个或者0个字符
# {n} 表示n个字符
# {n,m} 表示n-m个字符
# \s 表示一个空格
# 如果出现特殊字符需要用 \ 进行转义
# 如- 在正则表达式中表示为\-
# '''
# '''
# 例子：
# \d{3}\s+\d{3,8}
# \d{3}表示匹配3个数字，例如'010'；
# \s可以匹配一个空格（也包括Tab等空白符），所以\s+表示至少有一个空格，例如匹配' '，' '等；
# \d{3,8}表示3-8个数字，例如'1234567'
# '''
#
# '''
# 要做更精确地匹配，可以用[]表示范围,比如：
# [0-9a-zA-Z\_]可以匹配一个数字、字母或者下划线；
# [0-9a-zA-Z\_]+可以匹配至少由一个数字、字母或者下划线组成的字符串，比如'a100'，'0_Z'，'Py3000'等等；
# [a-zA-Z\_][0-9a-zA-Z\_]*可以匹配由字母或下划线开头，后接任意个由一个数字、字母或者下划线组成的字符串，也就是Python合法的变量；
# [a-zA-Z\_][0-9a-zA-Z\_]{0, 19}更精确地限制了变量的长度是1-20个字符（前面1个字符+后面最多19个字符）。
# '''
# import re
# test = '65465sa645fd'
# if re.match(r'\d{3}\s+\d{3,8}', test): # match()方法判断是否匹配
# print('ok')
# else:
# print('failed')
#
# # 切分字符串
# a = re.split(r'\s+', 'a b c')
# b = 'a b c'.split(' ') # 无法识别连续的空格
# print(a, b)
#
# # 用()表示的就是要提取的分组（Group）
# # ^(\d{3})-(\d{3,8})$分别定义了两个组，可以直接从匹配的字符串中提取出区号和本地号码
# m = re.match(r'^(\d{3})-(\d{3,8})$', '010-12345')
# # 正则表达式中定义了组，就可以在Match对象上用group()方法提取出子串来
# print(m, '\n', m.group(0), '\n', m.group(1), '\n', m.group(2))
#
# # 可以用re.compile()去编译正则表达式，那么接下来我们就可以重复使用时就不需要编译这个步骤了
#
#
# # datetime
# # 是python处理时间的标准库
# from datetime import datetime
# # 获取系统时间
# now = datetime.now() # 返回的类型是datetime
#
# # 获取指定日期和时间
# dt = datetime(2015, 4, 19, 12, 20) # 用指定日期时间创建datetime
#
# # datetime转换为timestamp
# dt.timestamp() # 把datetime转换为timestamp
# # Python的timestamp是一个浮点数。如果有小数位，小数位表示毫秒数
#
# # timestamp 转换为 datetime
# t = 1429417200.0
# datetime.fromtimestamp(t) # 在timestamp和本地时间做转换
# datetime.utcfromtimestamp(t) # UTC时间
#
# # str转换为datetime
# # '%Y-%m-%d %H:%M:%S'规定了日期和时间部分的格式
# cday = datetime.strptime('2015-6-1 18:19:59', '%Y-%m-%d %H:%M:%S')
# # datetime是没有时区信息的
#
# # datetime转换为str
# now.strftime('%a, %b %d %H:%M')
#
# # datetime加减
# # 加减可以直接用+和-运算符，不过需要导入timedelta这个类
# from datetime import datetime, timedelta
# now = datetime.now()
# print(now, now + timedelta(hours=10), now - timedelta(days=1), now + timedelta(days=2, hours=12))
#
# # 本地时间转换为UTC时间
# # 一个datetime类型有一个时区属性tzinfo，但是默认为None，所以无法区分这个datetime到底是哪个时区，除非强行给datetime设置一个时区
# from datetime import datetime, timedelta, timezone
# tz_utc_8 = timezone(timedelta(hours=8)) # 创建时区UTC+8:00
# print(datetime.now())
# print(datetime.now().replace(tzinfo=tz_utc_8)) # 强制设置为UTC+8:00
#
# # 时区转换
# # 先通过utcnow()拿到当前的UTC时间，再转换为任意时区的时间
# utc_dt = datetime.utcnow().replace(tzinfo=timezone.utc)
# print('当前的UTC时间', utc_dt)
# # astimezone()将转换时区为北京时间:
# bj_dt = utc_dt.astimezone(timezone(timedelta(hours=8)))
# print('北京时间：', bj_dt)
#
# '''
# 总结
# 时区转换的关键在于，拿到一个datetime时，要获知其正确的时区，然后强制设置时区，作为基准时间。
# 利用带时区的datetime，通过astimezone()方法，可以转换到任意时区。
# 注：不是必须从UTC+0:00时区转换到其他时区，任何带时区的datetime都可以正确转换，例如上述bj_dt到tokyo_dt的转换。
#
# datetime表示的时间需要时区信息才能确定一个特定的时间，否则只能视为本地时间。
# 如果要存储datetime，最佳方法是将其转换为timestamp再存储，因为timestamp的值与时区完全无关。
# '''
#
# # collections
# # collections是Python内建的一个集合模块，提供了许多有用的集合类
# # namedtuple是一个函数，它用来创建一个自定义的tuple对象，并且规定了tuple元素的个数，并可以用属性而不是索引来引用tuple的某个元素。
# # 这样一来，我们用namedtuple可以很方便地定义一种数据类型，它具备tuple的不变性，又可以根据属性来引用，使用十分方便
# from collections import namedtuple
# Point = namedtuple('Point', ['x', 'y'])
# p = Point(1,2)
# print(p, p.x, p.y)
#
# '''
# deque
# 使用list存储数据时，按索引访问元素很快，但是插入和删除元素就很慢了，因为list是线性存储，数据量大的时候，插入和删除效率很低。
# deque是为了高效实现插入和删除操作的双向列表，适合用于队列和栈
# deque除了实现list的append()和pop()外，还支持appendleft()和popleft()，这样就可以非常高效地往头部添加或删除元素
# '''
# from collections import deque
# q = deque(['a', 'b', 'c'])
# q.append('x') # 尾部进行插入
# q.appendleft('y') # 头部进行插入
# print(q)
#
# # defaultdict
# # 使用dict时，如果引用的Key不存在，就会抛出KeyError。如果希望key不存在时，返回一个默认值，就可以用defaultdict
# from collections import defaultdict
# dd = defaultdict(lambda: 'N/A')
# dd['key1'] = 'abc'
# print(dd['key1'])
# print(dd['key2']) # 不存在key2所以返回一个默认值
#
# # OrderedDict
# # 使用dict时，Key是无序的。在对dict做迭代时，我们无法确定Key的顺序。
# # 如果要保持Key的顺序，可以用OrderedDict
# from collections import OrderedDict
# d = dict([('a', 1), ('b', 2), ('c', 3)])
# print('d这个时候时无序的: ', d)
# d = OrderedDict([('a', 1), ('b', 2), ('c', 3)])
# print('d这个时候是有序的： ', d) # 可以用d.get('a')来获取值
#
# # OrderedDict可以实现一个FIFO（先进先出）的dict，当容量超出限制时，先删除最早添加的Key
# from collections import OrderedDict
#
#
# class LastUpdatedOrderedDict(OrderedDict):
#
# def __init__(self, capacity):
# super(LastUpdatedOrderedDict, self).__init__()
# self._capacity = capacity
#
# def __setitem__(self, key, value):
# containsKey = 1 if key in self else 0
# if len(self) - containsKey >= self._capacity:
# last = self.popitem(last=False)
# print('remove:', last)
# if containsKey:
# del self[key]
# print('set:', (key, value))
# else:
# print('add:', (key, value))
# OrderedDict.__setitem__(self, key, value)
#
# # Counter
# # Counter是一个简单的计数器，例如，统计字符出现的个数
# from collections import Counter
# c = Counter()
# for ch in 'hfeikfhae':
# c[ch] = c[ch] + 1
#
# print(c)
#
# # struct模块来解决bytes和其他二进制数据类型的转换
# # struct的pack函数把任意数据类型变成bytes
# import struct
# print(struct.pack('>I', 1024009999)) # >表示字节顺序是big-endian，也就是网络序，I表示4字节无符号整数
#
#
#
#
# import hashlib
#
# md5 = hashlib.md5()
# md5.update('how to use md5 in python hashlib?'.encode('utf-8'))
# print('MD5: ', md5.hexdigest())
#
# sha1 = hashlib.sha1()
# sha1.update('how to use sha1 in '.encode('utf-8'))
# sha1.update('python hashlib?'.encode('utf-8'))
# print('shal: ', sha1.hexdigest())
#
#
# '''
# itertools:
# count()会创建一个无限的迭代器
# cycle()会把传入的一个序列无限重复下去
# repeat()负责把一个元素无限重复下去，不过如果提供第二个参数就可以限定重复次数
# takewhile()等函数根据条件判断来截取出一个有限的序列
# chain()可以把一组迭代对象串联起来，形成一个更大的迭代器
# groupby()把迭代器中相邻的重复元素挑出来放在一起
#
# 总结：itertools模块提供的全部是处理迭代功能的函数，它们的返回值不是list，而是Iterator，只有用for循环迭代的时候才真正计算
# '''
#
#
# class Query(object):
#
# def __init__(self, name):
# self.name = name
#
# def __enter__(self):
# print('Begin')
# return self
#
# def __exit__(self, exc_type, exc_value, traceback):
# if exc_type:
# print('Error')
# else:
# print('End')
#
# def query(self):
# print('Query info about %s...' % self.name)
#
# with Query('Bob') as q:
# q.query()
#
#
# # 在某段代码执行前后自动执行特定代码
# # 例子：
# from contextlib import contextmanager
#
#
# @contextmanager # 简化上下文管理
# def tag(name):
# print("<%s>" % name)
# yield
# print("</%s>" % name)
#
# with tag("h1"):
# print("hello")
# print("world")
#
#
# # 如果一个对象没有实现上下文，我们就不能把它用于with语句。这个时候，可以用closing()来把该对象变为上下文对象
# # closing()的实现原理如下：
# @contextmanager
# def closing(thing):
# try:
# yield thing
# finally:
# thing.close()
#
#
# # 解析XML
# from xml.parsers.expat import ParserCreate
#
# class DefaultSaxHandler(object):
# def start_element(self, name, attrs):
# print('sax:start_element: %s, attrs: %s' % (name, str(attrs)))
#
# def end_element(self, name):
# print('sax:end_element: %s' % name)
#
# def char_data(self, text):
# print('sax:char_data: %s' % text)
#
# xml = r'''<?xml version="1.0"?>
# <ol>
# <li><a href="/python">Python</a></li>
# <li><a href="/ruby">Ruby</a></li>
# </ol>
# '''
#
# handler = DefaultSaxHandler()
# parser = ParserCreate()
# parser.StartElementHandler = handler.start_element
# parser.EndElementHandler = handler.end_element
# parser.CharacterDataHandler = handler.char_data
# parser.Parse(xml)
#
# # 解析HTML
# from html.parser import HTMLParser
# from html.entities import name2codepoint
#
#
# class MyHTMLParser(HTMLParser):
#
# def handle_starttag(self, tag, attrs):
# print('<%s>' % tag)
#
# def handle_endtag(self, tag):
# print('</%s>' % tag)
#
# def handle_startendtag(self, tag, attrs):
# print('<%s/>' % tag)
#
# def handle_data(self, data):
# print(data)
#
# def handle_comment(self, data):
# print('<!--', data, '-->')
#
# def handle_entityref(self, name):
# print('&%s;' % name)
#
# def handle_charref(self, name):
# print('&#%s;' % name)
#
# parser = MyHTMLParser()
# parser.feed('''<html>
# <head></head>
# <body>
# <!-- test html parser -->
# <p>Some <a href=\"#\">html</a> HTML tutorial...<br>END</p>
# </body></html>''')
#
# # 使用request对一个url抓取其返回的http响应
# from urllib import request
#
# with request.urlopen('https://api.douban.com/v2/book/2129650') as f:
# data = f.read()
# print('Status:', f.status, f.reason)
# for k, v in f.getheaders():
# print('%s: %s' % (k, v))
# print('Data:', data.decode('utf-8'))
#
# # 模拟浏览器发送GET请求，就需要使用Request对象，通过往Request对象添加HTTP头，我们就可以把请求伪装成浏览器
# from urllib import request
# req = request.Request('http://www.sina.com.cn/')
# # 添加HTTP头
# req.add_header('User-Agent', 'Mozilla/6.0 (iPhone; CPU iPhone OS 8_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/8.0 Mobile/10A5376e Safari/8536.25')
# with request.urlopen(req) as f:
# print('status', f.status, f.reason)
# for k, v in f.getheaders:
# print('%s: %s' % (k, v))
# print('Data:', f.read().decode('utf-8'))
from PIL import Image
# 打开一个jpg图像文件，注意是当前路径:
im = Image.open('test.jpg')
# 获得图像尺寸:
w, h = im.size
print('Original image size: %sx%s' % (w, h))
# 缩放到50%:
im.thumbnail((w//2, h//2))
print('Resize image to: %sx%s' % (w//2, h//2))
# 把缩放后的图像用jpeg格式保存:
im.save('thumbnails.png', 'png')
|
class Solution:
def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:
dum = head
cnt = 0
while dum:
dum = dum.next
cnt += 1
prev, cur = None, head
cnt -= n
while cnt > 0:
prev = cur
cur = cur.next
cnt -= 1
if prev:
prev.next = cur.next
else:
head = cur.next
return head
|
# -*- coding: utf-8 -*-
import scrapy
from qsbk.items import QsbkItem
from scrapy.http.response.html import HtmlResponse
from scrapy.selector.unified import SelectorList
class QsbkSpiderSpider(scrapy.Spider):
name = 'qsbk_spider'
allowed_domains = ['qiushibaike.com']
start_urls = ['https://www.qiushibaike.com/text/page/1/']
def parse(self, response):
content_lefts=response.xpath(".//div[@id='content-left']/div")
for content_left in content_lefts:
author=content_left.xpath(".//h2/text()").get().strip()
#get转码
content="".join(content_left.xpath(".//div[@class='content']//text()").getall()).strip()
# duanzi ={"author":author,"content":content}
item =QsbkItem(author=author,content=content)
yield item
next_url =response.xpath("//ul[@class='pagination']/li[last()]/a/@href").get()
if not next_url:
return
else:
nexturl="https://www.qiushibaike.com"+next_url
yield scrapy.Request(nexturl,self.parse)
#将一个个nexturl传给parse
#scrapy.request类，像url发送请求并用parse函数
|
from settings.development import *
|
import logging
from assertion import Assertion
logger = logging.getLogger( "TakenAssertion" )
CELL_DOMAIN = "cell"
# ROW_DOMAIN = "possibilities"
class TakenAssertion(Assertion):
def __init__(self):
super( TakenAssertion, self ).__init__()
def assertTuple(self, tuple):
#self.csp.domains[ CELL_DOMAIN ].taken.append( tuple.queencol )
pass
def retractTuple(self, tuple):
#self.csp.domains[ CELL_DOMAIN ].taken.remove( tuple.queencol )
pass
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''lisnp
Usage:
lisnp mm2yaml <file_name>...
lisnp yaml2mm <file_name>...
lisnp -h | --help
lisnp --version
Options:
-h --help Show this screen.
--version Show version.
'''
from __future__ import unicode_literals, print_function
# import elementtree.ElementTree as ET
import xml.etree.ElementTree as ET
import yaml
'''
TODO Replace ElementTree with defusedxml
19.6. XML vulnerabilities
https://docs.python.org/2/library/xml.html#xml-vulnerabilities
https://pypi.python.org/pypi/defusedxml/
These external packages are recommended for any code that parses untrusted XML data.
defusedxml is a pure Python package with modified subclasses of all stdlib XML parsers that prevent any potentially malicious operation. The package also ships with example exploits and extended documentation on more XML exploits like xpath injection.
defusedexpat provides a modified libexpat and patched replacement pyexpat extension module with countermeasures against entity expansion DoS attacks. Defusedexpat still allows a sane and configurable amount of entity expansions. The modifications will be merged into future releases of Python.
The workarounds and modifications are not included in patch releases as they break backward compatibility. After all inline DTD and entity expansion are well-defined XML features.
Example of use :
https://github.com/lorien/grab/pull/150/files?diff=split
'''
from docopt import docopt
import os
import os.path
__version__ = "0.1.0"
__author__ = "semi-automatique"
__license__ = "MIT"
def mm2yaml(mm_file_name):
print("linsp mm2yaml was called.")
if os.path.isfile(mm_file_name) and os.access(mm_file_name, os.R_OK):
print("File exists and is readable")
mm_file = ET.parse(mm_file_name)
print(mm_file)
# Next - write the file in yaml format.
yaml_file_name = os.path.splitext(mm_file_name)[0]+'.yml'
with open(yaml_file_name, 'w') as outfile:
# TODO Etudier yaml.safe_dump()
outfile.write( yaml.dump(mm_file, default_flow_style=False) )
else:
print("Either file is missing or is not readable")
def yaml2mm(yaml_file_name):
''' There is no guarantee for the moment that a mind map convert to YAML and back to mind map format will have all attributes at the same position in the new mind map. '''
print("linsp yaml2mm was called.")
if os.path.isfile(yaml_file_name) and os.access(yaml_file_name, os.R_OK):
print("File exists and is readable")
with open(yaml_file_name, 'r') as stream:
yaml_file = yaml.load(stream)
print(yaml_file)
# Next - write the file in mm format.
mm_file_name = os.path.splitext(yaml_file_name)[0]+'.mm'
with open(mm_file_name, 'w') as outfile:
root = yaml_file.getroot()
print(ET.tostring(root, "utf-8"))
yaml_file.write(outfile)
else:
print("Either file is missing or is not readable")
def main():
'''Main entry point for the lisnp CLI.'''
args = docopt(__doc__, version=__version__)
print(args)
file_name = args.get('<file_name>')[0]
print(file_name)
if args.get('mm2yaml'):
mm2yaml(file_name)
if args.get('yaml2mm'):
yaml2mm(file_name)
if __name__ == '__main__':
main()
|
from config import *
import random
import string
def generate():
link = ''.join(random.choice(string.uppercase+string.lowercase+string.digits) for x in range(5))
while db.webm.find_one({"short":link}):
link = ''.join(random.choice(string.uppercase+string.lowercase+string.digits) for x in range(5))
return link
#db.links.insert({"short":link, "path":"/test/path/to/file", "user":user, "points":0, "comments":[{}]})
# this is what the coments section should look like:
'''
[
{
"user":user,
"points":0
"quotes":
[
{
"user":user,
"points":0
}
]
},
{
"user":user,
"points":0
"quotes":
[
{
"user":user,
"points":0
}
]
},
]
'''
|
from meterbus.meterbus import meterbus
import logging
__name__ = 'meterbus api'
__version__ = '0.1'
|
from django.contrib.auth.models import User
from django.db import models
from quizApp.models import Quiz
class Attempted(models.Model):
user = models.ForeignKey(User, on_delete=models.CASCADE)
quiz = models.ForeignKey(Quiz, on_delete=models.CASCADE)
got = models.IntegerField()
created = models.DateTimeField(auto_now_add=True)
def __str__(self):
return self.user.username
class Meta:
verbose_name_plural = 'Attempted Quizzes'
|
import pytest
from elections.tests.factories import ElectedRoleFactory
from elections.utils import ElectionBuilder
from organisations.tests.factories import (
OrganisationDivisionFactory,
OrganisationDivisionSetFactory,
)
def test_division_set_by_date(db):
"""
Test that we can get a division set by a given date
"""
END_DATE = "2025-05-03"
FUTURE_DATE = "2025-05-05"
ds = OrganisationDivisionSetFactory(end_date=END_DATE)
for i in range(10):
org_div = OrganisationDivisionFactory(divisionset=ds)
org = org_div.organisation
ElectedRoleFactory(organisation=org)
def _make_ids_for_date(date):
x = ElectionBuilder("local", date)
x.with_organisation(org)
x.with_division(org_div)
return x
assert _make_ids_for_date(END_DATE)
with pytest.raises(ValueError) as excinfo:
_make_ids_for_date(FUTURE_DATE)
assert "DivisionSet end date before election date" in str(excinfo.value)
|
from enum import Enum
class Const(Enum):
CommonPhrasesContainer = '29914481-fef8-4e62-b774-f5dc31fff4d2'
|
from django.conf.urls import url
from views import *
urlpatterns = [
#resource lists
url(r'^$', home, name = 'home'),
url(r'search_types$', search_types, name = 'search_types'),
url(r'resource_type/(?P<resource_type_id>\d+)$', resource_type, name = 'resource_type'),
url(r'resource_list$', resource_list, name = 'resource_list'),
# individual resources
url(r'view_resource/(?P<resource_id>\d+)$', view_resource, name = 'view_resource'),
url(r'edit_resource/(?P<resource_id>\d+)$', edit_resource, name = 'edit_resource'),
url(r'confirm_delete/(?P<resource_id>\d+)$', confirm_delete, name = 'confirm_delete'),
url(r'delete_resource$', delete_resource, name = 'delete_resource'),
url(r'save_resource/(?P<resource_id>\d+)$', save_resource, name = 'save_resource'),
url(r'add_resource$', add_resource, name = 'add_resource'),
url(r'submit_resource$', submit_resource, name = 'submit_resource'),
# output
url(r'pdf_print_resources$', pdf_print_resources, name = 'pdf_print_resources'),
url(r'csv_print_resources$', csv_print_resources, name = 'csv_print_resources'),
]
|
import numpy as np
import pandas as pd
from sklearn.base import TransformerMixin
from sklearn.pipeline import Pipeline, FeatureUnion
from sklearn.preprocessing import StandardScaler
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer, SnowballStemmer, WordNetLemmatizer
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.decomposition import NMF, LatentDirichletAllocation
from sklearn.grid_search import GridSearchCV
from sklearn.metrics import accuracy_score, precision_score, recall_score, confusion_matrix
from sklearn.cross_validation import train_test_split, KFold, StratifiedKFold
from collections import Counter, OrderedDict
import re
import time
import string
import en
from datetime import datetime
import cPickle as pickle
import exploratory_analysis as eda
start = datetime.now()
class CustomMixin(TransformerMixin):
def get_params(self, **kwargs):
return dict()
def set_params(self, **kwargs):
for key in self.get_params():
setattr(self, key, kwargs[key])
return self
class CleanSAT(CustomMixin):
def fit(self, X, y):
self.median_score = X[(X['Highest Composite SAT Score']<=2400) & (X['Highest Composite SAT Score']>=600)]['Highest Composite SAT Score'].median()
self.median_times = X['How many times did you take the official SAT?'].median()
return self
def transform(self, X):
# Remove the impossible scores first
X['Highest Composite SAT Score'] = X['Highest Composite SAT Score'].apply(lambda x: None if x>2400 or x<600 else x)
# Parse out the scores from the breakdown columns
X['SAT_total_temp'] = X['Highest SAT Scores'].apply(lambda x: self.parseSAT(x) if type(x)==str else x)
self.finalizeScores(X)
# Give times taken a shorter name
X['SAT_times_taken'] = X['How many times did you take the official SAT?'].copy()
self.impute(X)
lap = datetime.now()
print 'Finished SAT after {} seconds.'.format((lap-start).seconds)
return X
def impute(self, X):
'''
Impute missing values
'''
X['SAT_total_final'].fillna(value=self.median_score, inplace=True)
X['SAT_times_taken'].fillna(value=self.median_times, inplace=True)
def parseSAT(self, x):
'''
Show logic tree in the docstring
'''
scores = [float(i) for i in x.split()]
if scores[-1] > 800:
if scores[-1] > 1600: # If the rightmost score is >1600, then it is the 2400-scale score
return scores[-1]
else: # The following chunk is for scores between 800 and 1600
if sum(scores[:-1]) == scores[-1]: # If sum of breakdown == rightmost score
if len(scores[:-1]) == 3: # If 3 scores, must be 2400-scale
return scores[-1]
elif len(scores[:-1]) == 2: # If 2 scores, must be 1600-scale
return scores[-1]/1600.*2400
else:
return np.nan # Cannot be parsed
elif sum(scores[:-1]) < scores[-1]:
if len(scores[:-1]) == 2: # If 2 scores, must be 2400-scale
return scores[-1]
else:
return np.nan # Cannot be parsed
else: # If the rightmost score is <=800
if len(scores) == 3: # If 3 scores, it must be 2400-scale
return sum(scores)
elif len(scores) == 2: # If 2 scores, it must be 1600-scale
return sum(scores)/1600.*2400
else:
return np.nan # Cannot be parsed
def finalizeScores(self, X):
# Change NaNs to None in SAT_total_temp so we can apply a max function
X['SAT_total_temp'] = X['SAT_total_temp'].apply(lambda x: None if str(x)=='nan' else x)
# Take max of 2 columns
X['SAT_total_final'] = np.max(X[['Highest Composite SAT Score','SAT_total_temp']], axis=1)
# Remove faulty entries that don't end in '0' (SAT scores are multiples of 10)
X['SAT_total_final'] = X['SAT_total_final'].apply(lambda x: None if x%10>0 else x)
class CleanGPA(CustomMixin):
def fit(self, X, y):
self.median = X[(X['High School GPA']<=4) & (X['High School GPA']>2) ]['High School GPA'].median()
return self
def transform(self, X):
X['High School GPA'] = X['High School GPA'].apply(lambda x: np.nan if x>100 or x<=2 else x)
X['High School GPA'] = X['High School GPA'].apply(lambda x: self.median if x>4 else x)
self.impute(X)
lap = datetime.now()
print 'Finished GPA after {} seconds.'.format((lap-start).seconds)
return X
def impute(self, X):
X['High School GPA'].fillna(value=self.median, inplace=True)
class Gender(CustomMixin):
def fit(self, X, y):
X['Male'] = X['Gender'].apply(lambda x: 1 if x=='Male' else 0)
self.mode = X['Male'].mode()
return self
def transform(self, X):
X['Male'] = X['Gender'].apply(lambda x: 1 if x=='Male' else 0)
self.impute(X)
lap = datetime.now()
print 'Finished Gender after {} seconds.'.format((lap-start).seconds)
return X
def impute(self, X):
X['Male'].fillna(value=self.mode, inplace=True)
class Ethnicity(CustomMixin):
def fit(self, X, y):
self.ethnicity_cols = ['Ethnicity_Asian', 'Ethnicity_Black', 'Ethnicity_Hispanic', 'Ethnicity_White', 'Ethnicity_Pacific', 'Ethnicity_NativeAm']
self.ethnicity_words = ['asian', 'black / african american', 'hispanic', 'white non-hispanic', 'native hawaiian / pacific islander', 'native american']
return self
def transform(self, X):
self.extract(X)
self.impute(X)
lap = datetime.now()
print 'Finished Ethnicity after {} seconds.'.format((lap-start).seconds)
return X
def impute(self, X):
for col in self.ethnicity_cols:
X[col].fillna(value=0, inplace=True)
def extract(self, X):
X['Ethnicity2'] = X['Ethnicity'].apply(lambda x: self.cleanEthnicity(x) if type(x)==str else x)
for col,word in zip(self.ethnicity_cols, self.ethnicity_words):
X[col] = X['Ethnicity2'].apply(lambda x: 1 if type(x)==list and word in x else 0)
def cleanEthnicity(self, x):
x = x.lower().split('|')
if 'prefer not to share' in x:
del x[x.index('prefer not to share')]
if len(x) == 0:
return np.nan
else:
return x
class ExtraCurriculars(CustomMixin):
def fit(self, X, y):
leader_words = ['leader','president','founder']
arts_words = ['arts', 'music', 'jazz', 'band', 'orchestra', 'choir', 'drama', 'theater']
award_words = ['award', 'scholarship', 'achievement', 'prize']
community_words = ['volunteer', 'community','cleanup', 'ngo', 'environment', 'humanity','green', 'charity']
academic_words = ['science', 'math', 'engineering']
gov_words = ['debate', 'model', 'government']
diversity_words = ['alliance', 'multicultural', 'diversity']
race_words = ['naacp','asian','jewish','german','french','japanese','italian','chinese']
self.lst_of_keywords = [leader_words, arts_words, award_words, community_words, academic_words, gov_words, diversity_words, race_words]
self.cols = ['leader', 'arts', 'award', 'community', 'academic', 'gov', 'diversity', 'race_ecc']
return self
def transform(self, X):
for col,lst in zip(self.cols, self.lst_of_keywords):
X[col] = X['High School Extracurricular Activities'].apply(lambda x: self.extract(x, lst))
lap = datetime.now()
print 'Finished ECC after {} seconds.'.format((lap-start).seconds)
return X
def impute(self, X):
for col in self.cols:
X[col].fillna(value=0, inplace=True)
def extract(self, x, lst):
'''
INPUT:
OUTPUT:
'''
if type(x)==str:
x = x.lower()
for word in lst:
if x.find(word)>-1:
return 1
return 0
else:
return 0
class HomeCountry(CustomMixin):
def fit(self, X, y):
self.extract(X)
self.mode = X['Home Country_US'].mode()
return self
def transform(self, X):
self.extract(X)
self.impute(X)
lap = datetime.now()
print 'Finished HomeCountry after {} seconds.'.format((lap-start).seconds)
return X
def impute(self, X):
X['Home Country_US'].fillna(self.mode)
def extract(self, X):
regex = re.compile('[[]\S+[]]\s[[]\S+[]]\s(.+)')
get_country = lambda x: regex.findall(x)[0] if not x is np.nan and not x is None and len(regex.findall(x))>0 else x
X['Home Country'] = X['Home Country'].apply(get_country)
X['Home Country_US'] = X['Home Country'].apply(lambda x: 1 if x=='United States' else 0)
class Sports(CustomMixin):
def fit(self, X, y):
all_sports = list(X['High School Sports Played'].apply(eda.getAllSports))
self.unique_sports = eda.getUniqueSports(all_sports)
return self
def transform(self, X):
# Initialize dummy variables for each sport category, set to 0s.
# for sport in self.unique_sports:
# X['sports_'+sport] = 0
# Fill in the dummy variables for each sport category (1 or 0).
# eda.parseSports(X, self.unique_sports)
regexp = re.compile('[[]\S+[]]\s[[]\S+[]]\s(.+)')
# Create a sportsVarsity dummy variable
X['sportsVarsity'] = X['High School Sports Played'].apply(lambda x: eda.parseVarsity(x, self.unique_sports, regexp))
# Create a sportsCaptain dummy variable.
X['sportsCaptain'] = X['High School Sports Played'].apply(lambda x: eda.parseCaptain(x, self.unique_sports, regexp))
lap = datetime.now()
print 'Finished Sports after {} seconds.'.format((lap-start).seconds)
return X
class DummifyCategoricals(CustomMixin):
def fit(self, X, y):
return self
def transform(self, X):
X = pd.get_dummies(X, columns=['Academic Performance in High School'], prefix='HS')
lap = datetime.now()
print 'Finished Dummify after {} seconds.'.format((lap-start).seconds)
return X
class FinalColumns(CustomMixin):
def fit(self, X, y):
return self
def transform(self, X):
final_cols = ['SAT_total_final', 'SAT_times_taken', 'High School GPA', 'Male', 'leader', 'arts', 'award', 'community', 'academic', 'gov', 'diversity', 'race_ecc', 'Home Country_US']
ethnicity_cols = [col for col in X.columns if col.find('Ethnicity_')>-1]
HS_perf_cols = [col for col in X.columns if col.find('HS_')>-1]
sports_cols = ['sportsVarsity', 'sportsCaptain']
final_cols.extend(ethnicity_cols)
final_cols.remove('Ethnicity_White') # Only need n-1 dummy vars
final_cols.extend(HS_perf_cols)
#final_cols.remove('HS_Steady') # Only need n-1 dummy vars
final_cols.extend(sports_cols)
final_cols.remove('High School GPA') # Due to multi-collinearity w/ SAT
good_cols = ['SAT_total_final', 'SAT_times_taken', 'High School GPA', 'Male', 'leader', 'award', 'academic', 'gov', 'sportsVarsity', 'sportsCaptain', 'Ethnicity_Black', 'Ethnicity_White', 'HS_Steady']
X_model = X[final_cols].copy()
print X_model.isnull().sum()
lap = datetime.now()
print 'Finished FinalColumns after {} seconds.'.format((lap-start).seconds)
return X_model
class FinalColumnsWithEssay(CustomMixin):
def fit(self, X, y):
return self
def transform(self, X):
final_cols = ['SAT_total_final', 'SAT_times_taken', 'High School GPA', 'Male', 'leader', 'arts', 'award', 'community', 'academic', 'gov', 'diversity', 'race_ecc', 'Home Country_US']
ethnicity_cols = [col for col in X.columns if col.find('Ethnicity_')>-1]
HS_perf_cols = [col for col in X.columns if col.find('HS_')>-1]
sports_cols = ['sportsVarsity', 'sportsCaptain']
essay_cols = ['5000_words_frac', 'essay_topic1', 'essay_topic2', 'essay_topic3', 'essay_topic4', 'essay_topic5', 'essay_topic6', 'essay_topic7']
final_cols.extend(ethnicity_cols)
final_cols.remove('Ethnicity_White') # Only need n-1 dummy vars
final_cols.extend(HS_perf_cols)
final_cols.remove('HS_Steady') # Only need n-1 dummy vars
final_cols.extend(sports_cols)
final_cols.remove('High School GPA') # Due to multi-collinearity w/ SAT
final_cols.extend(essay_cols)
X_model = X[final_cols].copy()
lap = datetime.now()
print 'Finished FinalColumnsWithEssay after {} seconds.'.format((lap-start).seconds)
return X_model
final_cols = ['SAT_total_final','SAT_times_taken', 'male', 'leader','arts', 'award', 'community', 'academic', 'gov', 'diversity', 'race_ecc', 'Home Country_US', 'Ethnicity_Asian', 'Ethnicity_Black', 'Ethnicity_Hispanic', 'Ethnicity_Pacific', 'Ethnicity_NativeAm', 'HS_High at first but got worse', 'HS_Low at first but improved', 'HS_Low one semester/year', 'HS_Some good some bad','sportsVarsity', 'sportsCaptain']
|
# encoding:utf-8
from __future__ import unicode_literals
from django.contrib import admin
from helpers.director.shortcut import TablePage,ModelTable,page_dc,FormPage,ModelFields,model_dc,\
regist_director,TabGroup,RowFilter,permit_list,has_permit
from .models import JianFangInfo,CunWei,Policy,ApplyTable,YinJiZhengGai,JianguanInfo
from helpers.maintenance.update_static_timestamp import js_stamp
import json
# Register your models here.
from django.utils.html import escape
class JianFangInfoTablePage(TablePage):
template='liantang/jianfang.html'
def get_path(self):
path = [
{'label':'建房信息','url':'/pc/xxx'}
]
return path
class JianFangInfoTable(ModelTable):
model = JianFangInfo
exclude=['shenqing','xieyi','xiugai','other']
def dict_row(self, inst):
return {
'cunwei':unicode(inst.cunwei),
'yinji':inst.yinjizhenggai_set.last().get_state() if inst.yinjizhenggai_set.last() else "",
'shenqing':json.loads(inst.shenqing) if inst.shenqing else {}
}
def get_heads(self):
heads = super(self.__class__,self).get_heads()
heads.append({
'name':'yinji',
'label':'应急整改'
})
return heads
class JianfangFilter(RowFilter):
model=JianFangInfo
names=['cunwei','state','zhenggai']
range_fields =[{'name':'date','type':'date'}]
def get_context(self):
ls=super(self.__class__,self).get_context()
option=[
{'value':'no_zhenggai','label':'无整改'},
{'value':'zhenggai_ing','label':'整改中'},
{'value':'zhenggai_over','label':'已整改'},
]
ls.append({'name':'zhenggai','label':'应急整改','options':option})
for dc in ls:
if dc['name']=='state':
dc['config']={
'orgin_order':True
}
return ls
def get_query(self, query):
yinji = self.filter_args.pop('zhenggai',None)
if yinji=='no_zhenggai':
query = query.filter(yinjizhenggai__isnull=True)
elif yinji=='zhenggai_ing':
query = query.filter(yinjizhenggai__isnull=False)
query= query.filter(yinjizhenggai__state=1).distinct()
elif yinji=='zhenggai_over':
query = query.filter(yinjizhenggai__isnull=False)
query = query.exclude(yinjizhenggai__state=1).distinct()
# if yinji=='zhenggai_ing':
# query = query.filter(yinjizhenggai__isnull=False)
# if yinji=='has_zhenggai':
# query = query.filter(yinjizhenggai__isnull=False)
# elif yinji=='no_zhenggai':
# query = query.filter(yinjizhenggai__isnull=True)
return super(self.__class__,self).get_query(query)
JianFangInfoTable.filters=JianfangFilter
class JianFangInfoFormPage(FormPage):
# ex_js=('/static/js/inputs_uis.pack.js?t=%s'%js_stamp.inputs_uis_pack_js,)
template = 'liantang/jianfang_form.html'
class JianFangInfoForm(ModelFields):
class Meta:
model = JianFangInfo
exclude=[]
def __init__(self, dc={},*args,**kw):
if dc.get('shenqing'):
dc['shenqing'] = json.dumps(dc['shenqing'])
ModelFields.__init__(self,dc,*args,**kw)
def get_heads(self):
heads = super(self.__class__,self).get_heads()
heads.append({
'name':'yinji',
'type':'linetext',
'label':'应急整改'
})
return heads
def get_row(self):
row = ModelFields.get_row(self)
row['shenqing'] = json.loads(self.instance.shenqing) if self.instance.shenqing else {}
return row
def dict_head(self, head):
if head['name']=='date':
head['type']='date'
elif head['name'] == 'state':
head['config']={
'orgin_order':True
}
return head
def get_readonly_fields(self):
readonly_fields = ModelFields.get_readonly_fields(self)
# 只能首次修改
if self.instance.pk and has_permit(self.crt_user,'liantang.-only_first_edit'):
readonly_fields.extend(['name','date','cunwei','addr','phone','state'])
return readonly_fields
def get_context(self):
ctx = ModelFields.get_context(self)
if has_permit(self.crt_user,'liantang.-only_add'):
ctx['only_add']=True
return ctx
class YinJiTablePage(TablePage):
template='liantang/yingji_tab.html'
page_label='应急整改'
class YinjiTable(ModelTable):
model=YinJiZhengGai
exclude=['jianfang','file']
def __init__(self, *args,**kws):
ModelTable.__init__(self,*args,**kws)
jianfang_pk = self.kw.get('pk')
self.jianfang = JianFangInfo.objects.get(pk = jianfang_pk)
def inn_filter(self, query):
return query.filter(jianfang=self.jianfang)
class YinJiFormPage(FormPage):
#ex_js=('/static/js/inputs_uis.pack.js?t=%s'%js_stamp.inputs_uis_pack_js,)
template='liantang/yinji_form.html'
class YinjiForm(ModelFields):
class Meta:
model = YinJiZhengGai
exclude =['jianfang']
def __init__(self, *args,**kws):
super(self.__class__,self).__init__(*args,**kws)
if not self.instance.pk and self.kw.has_key('jianfang_pk'):
jianfang_pk = self.kw.get('jianfang_pk')
jianfang = JianFangInfo.objects.get(pk = jianfang_pk)
self.instance.jianfang = jianfang
def dict_head(self, head):
if head['name']=='date':
head['type']='date'
elif head['name']=='file':
head['type'] = 'field-file-uploader'
return head
def get_readonly_fields(self):
readonly_fields = ModelFields.get_readonly_fields(self)
# 只能首次修改
if self.instance.pk and has_permit(self.crt_user,'liantang.-only_first_edit'):
readonly_fields.extend(['state','date','desp'])
return readonly_fields
def get_context(self):
ctx = ModelFields.get_context(self)
if has_permit(self.crt_user,'liantang.-only_add'):
ctx['only_add']=True
return ctx
class JianguanInfoFormPage(FormPage):
template='liantang/jianguan_info_form.html'
class fieldsCls(ModelFields):
def __init__(self,dc={}, *args,**kws):
if dc.get('qianqi_zhunbei'):
dc['qianqi_zhunbei'] = json.dumps(dc['qianqi_zhunbei'])
if dc.get('zaijian_jianguan'):
dc['zaijian_jianguan'] = json.dumps(dc['zaijian_jianguan'])
if dc.get('jungong_yanshou'):
dc['jungong_yanshou'] = json.dumps(dc['jungong_yanshou'])
jianfang_pk = kws.get('pk')
if jianfang_pk:
jianfang_info = JianFangInfo.objects.get(pk = jianfang_pk)
instance,_ = JianguanInfo.objects.get_or_create(jianfang = jianfang_info)
dc['pk'] = instance.pk
ModelFields.__init__(self,dc=dc, *args,**kws)
class Meta:
model=JianguanInfo
exclude = []
def get_row(self):
dc = ModelFields.get_row(self)
dc['qianqi_zhunbei']=json.loads(self.instance.qianqi_zhunbei) if self.instance.qianqi_zhunbei else {}
dc['zaijian_jianguan'] = json.loads(dc['zaijian_jianguan']) if dc.get('zaijian_jianguan') else {}
dc['jungong_yanshou']= json.loads(dc['jungong_yanshou']) if dc.get('jungong_yanshou') else {}
return dc
def get_context(self):
ctx = ModelFields.get_context(self)
if has_permit(self.crt_user,'liantang.-only_add'):
ctx['only_add']=True
return ctx
class JianFangGroup(TabGroup):
def __init__(self, request):
pk =request.GET.get('pk')
if pk:
self.jianfanginfo = JianFangInfo.objects.get(pk=pk)
else:
self.jianfanginfo =None
TabGroup.__init__(self,request)
def get_tabs(self):
if self.jianfanginfo:
count = self.jianfanginfo.yinjizhenggai_set.count()
tabs =[{'name':'blockgroup_normal','label':'基本信息','page_cls':JianFangInfoFormPage},
{'name':'jianguan_info','label':'监管信息','page_cls':JianguanInfoFormPage},
{'name':'blockgroup_map','label':'应急整改(%s)'%count,'page_cls':YinJiTablePage},
]
else:
tabs=[{'name':'blockgroup_normal','label':'基本信息','page_cls':JianFangInfoFormPage},]
return tabs
def get_label(self):
if self.jianfanginfo:
return unicode(self.jianfanginfo)
else:
return '新建建房申请'
class CunWeiTablePage(TablePage):
class CunWeiTable(ModelTable):
model = CunWei
exclude = []
class CunWeiFormPage(FormPage):
class CunWeiForm(ModelFields):
class Meta:
model = CunWei
exclude =[]
class PolicyTablePage(TablePage):
class PolicyTable(ModelTable):
model = Policy
exclude=[]
def dict_row(self, inst):
dc={
'file':'<a href="%s" target="_blank">查看</a>'%inst.file if inst.file else '',
'desp':escape(inst.desp)
}
return dc
class PolicyFormPage(FormPage):
ex_js=('/static/js/inputs_uis.pack.js?t=%s'%js_stamp.inputs_uis_pack_js,)
class PolicyForm(ModelFields):
class Meta:
model = Policy
exclude = []
def dict_head(self, head):
if head['name'] == 'file':
head['type'] = 'field-file-uploader'
head['config']={
'accept':'application/pdf,image/*',
'sortable':False,
'multiple':False
}
return head
class ApplyTableTablePage(TablePage):
class ApplyTable(ModelTable):
model = ApplyTable
exclude =[]
def dict_row(self, inst):
dc={
'file':'<a href="%s" target="_blank">查看</a>'%inst.file if inst.file else ''
}
return dc
class ApplyTableFormPage(FormPage):
ex_js=('/static/js/inputs_uis.pack.js?t=%s'%js_stamp.inputs_uis_pack_js,)
class ApplyTableForm(ModelFields):
class Meta:
model = ApplyTable
exclude = []
def dict_head(self, head):
if head['name'] == 'file':
head['type'] = 'field-file-uploader'
head['config']={
'accept':'application/pdf,image/*',
'sortable':False,
'multiple':False
}
return head
model_dc[JianFangInfo] = {'fields':JianFangInfoFormPage.JianFangInfoForm}
model_dc[CunWei] = {'fields':CunWeiFormPage.CunWeiForm}
model_dc[Policy]={'fields':PolicyFormPage.PolicyForm}
model_dc[ApplyTable]={'fields':ApplyTableFormPage.ApplyTableForm}
model_dc[YinJiZhengGai]={'fields':YinJiFormPage.YinjiForm}
model_dc[JianguanInfo]={'fields':JianguanInfoFormPage.fieldsCls}
page_dc.update({
'liantang.jianfanginfo':JianFangInfoTablePage,
'liantang.jianfanginfo.edit':JianFangGroup, #JianFangInfoFormPage,
'liantang.cunwei':CunWeiTablePage,
'liantang.cunwei.edit':CunWeiFormPage,
'liantang.policy':PolicyTablePage,
'liantang.policy.edit':PolicyFormPage,
'liantang.applytable':ApplyTableTablePage,
'liantang.applytable.edit':ApplyTableFormPage,
'liantang.yinji.edit':YinJiFormPage,
})
permit_list.append(CunWei)
permit_list.append(JianFangInfo)
permit_list.append(YinJiZhengGai)
permit_list.append(Policy)
permit_list.append(ApplyTable)
permit_list.append(JianguanInfo)
permit_list.append({'name':'liantang','label':'建房信息乱改约束',
'fields':[
{'name':'-only_add','label':'只能添加建房信息文件','type':'bool'},
{'name':'-only_first_edit','label':'只能首次编辑建房信息','type':'bool'},
]
})
|
from tkinter import *
from tkinter.dialog import *
from tkinter.messagebox import *
from tkinter.ttk import *
# 第一个窗口
'''
def xinlabel(event):
global xin
s = Label(xin, text = "我爱Python")
s.pack()
xin = Tk()
#b1 = Button(xin, text = "Click Me", command = xinlabel)
b1 = Button(xin, text = "Click Me")
b1.bind("<Button-1>", xinlabel)
b1.pack()
xin.mainloop()
'''
# 按钮
'''
xin = Tk()
b1 = Button(xin, text = "星哥")
b1['width'] = 25
b1['height'] = 4
b1.pack()
b2 = Button(xin, text = "雷肥")
b2['width'] = 20
b2['height'] = 4
b2['background'] = 'red'
b2.pack()
xin.mainloop()
'''
# Pack布局
'''
root = Tk()
Button(root, text = 'A').pack(side = LEFT, expand = YES, fill = Y)
Button(root, text = 'B').pack(side = TOP, expand = YES, fill = BOTH)
Button(root, text = 'C').pack(side = RIGHT, expand = YES, fill = NONE, anchor = NE)
Button(root, text = 'D').pack(side = LEFT, expand = NO, fill = Y)
Button(root, text = 'E').pack(side = TOP, expand = NO, fill = BOTH)
Button(root, text = 'F').pack(side = BOTTOM, expand = YES)
Button(root, text = 'G').pack(anchor = SE)
root.mainloop()
'''
# 登录窗口
def on_click(event):
s1 = e1.get()
s2 = e2.get()
l1 = len(s1)
l2 = len(s2)
if s1 == "qiao" and s2 == "wazying":
c['text'] = "登录成功"
else:
c['text'] = "用户名或密码错误"
e1.delete(0, l1)
e2.delete(0, l2)
xin = Tk()
Label(xin, text = "账号：").grid(row = 0, sticky = W)
e1 = Entry(xin)
e1.grid(row = 0, column = 1, sticky = E)
Label(xin, text = "密码：").grid(row = 1, sticky = W)
e2 = Entry(xin)
e2['show'] = '*'
e2.grid(row = 1, column = 1, sticky = E)
b = Button(xin, text = "登录")
b.grid(row = 2, column = 1, sticky = E)
b.bind('<Button-1>', on_click)
c = Label(xin, text = "")
c.grid(row = 3)
xin.mainloop()
# 菜单
'''
root = Tk()
menubar = Menu(root)
fmenu = Menu(menubar)
for item in ['新建', '打开', '保存', '另存为']:
fmenu.add_command(label = item)
emenu = Menu(menubar)
for item in ['复制', '粘贴', '剪切']:
emenu.add_command(label = item)
vmenu = Menu(menubar)
for item in ['默认视图', '新式视图']:
vmenu.add_command(label = item)
amenu = Menu(menubar)
for item in ['版权信息', '其他说明']:
amenu.add_command(label = item)
menubar.add_cascade(label = '文件', menu = fmenu)
menubar.add_cascade(label = '编辑', menu = emenu)
menubar.add_cascade(label = '视图', menu = vmenu)
menubar.add_cascade(label = '关于', menu = amenu)
root['menu'] = menubar
root.mainloop()
'''
# 右键弹出菜单
'''
def xin():
global root
Label(root, text = "I love python").pack()
def pop(event):
menubar.post(event.x_root, event.y_root)
root = Tk()
menubar = Menu(root)
for item in ['vb', 'c/c++', 'java', 'php']:
menubar.add_command(label = item)
menubar.add_command(label = 'python', command = xin)
root.bind('<Button-3>', pop)
root.mainloop()
'''
# 菜单中的分隔符
'''
def on_click():
global root
Label(root, text = "hello").pack()
root = Tk()
menubar = Menu(root)
submenu = Menu(menubar)
for item in ['python', 'perl', 'php', 'ruby']:
submenu.add_command(label = item, command = on_click)
submenu.add_separator()
for item in ['java', 'c++', 'c']:
submenu.add_command(label = item, command = on_click)
menubar.add_cascade(label = 'lan', menu = submenu)
root['menu'] = menubar
root.mainloop()
'''
# 对话框
'''
def xin():
d = Dialog(None, title = "2014CHINA", text = "Do you know?",
bitmap = DIALOG_ICON, default = 0, strings = ('yes', 'not sure', 'no'))
print(d.num)
t = Button(None, text = "This is a research", command = xin)
t.pack()
b = Button(None, text = "Close", command = t.quit)
b.pack()
t.mainloop()
'''
# Checkbutton
'''
time1 = 0
time2 = 0
def xin1():
global l, c1, time1
if time1 % 2 == 0:
time1 += 1
l['text'] = '2014被选中'
else:
time1 += 1
l['text'] = '2014被取消'
def xin2():
global l, c2, time2
if time2 % 2 == 0:
time2 += 1
l['text'] = '2015被选中'
else:
time2 += 1
l['text'] = '2015被取消'
root = Tk()
c1 = Checkbutton(root, text = '2014', command = xin1)
c2 = Checkbutton(root, text = '2015', command = xin2)
l = Label(root, text = ' ')
c1.pack()
c2.pack()
l.pack()
root.mainloop()
'''
# 富文本
'''
root = Tk()
t = Text(root, width = 50, height = 30)
t.pack()
root.mainloop()
'''
# 多窗口
'''
def xin():
global root
f = Toplevel(root, width = 30, height = 20)
f.title("我是toplevel")
lf = Label(f, text = "我是toplevel")
lf.pack()
root = Tk()
root.title("我是root窗口")
l = Label(root, text = "我属于root")
b = Button(root, text = "点击弹出新窗口", command = xin)
l.pack()
b.pack()
root.mainloop()
'''
# Canvas
'''
root = Tk()
root.geometry('400x450+450+100')
#root.overrideredirect(1)
root.title("中国象棋")
can = Canvas(root, width = 400, height = 450)
can.create_line((0, 2), (400, 2), width = 1)
for i in range(10):
can.create_line((0, i*50), (400, i*50), width = 1)
can.create_line((3, 0), (3, 450), width = 2)
for i in range(8):
can.create_line((i*50, 0), (i*50, 200), width = 1)
for i in range(8):
can.create_line((i*50, 250), (i*50, 450), width = 1)
can.create_line((397, 0), (397, 450), width = 1)
can.create_line((150, 0), (250, 100), width = 1)
can.create_line((150, 100), (250, 0), width = 1)
can.create_line((150, 450), (250, 350), width = 1)
can.create_line((150, 350), (250, 450), width = 1)
can.create_text(20, 220, text = "楚河")
can.create_text(380, 220, text = "汉界")
can.pack()
root.mainloop()
'''
|
import psycopg2
from app import config
class MasterDAO:
"""
Master DAO class from which all DAO classes inherit their connection
to the PostgresSQL database using psycopg2.
"""
def __init__(self):
"""
Initializes the MasterDAO object.
Used to give the inheriting classes their connections to the
database.
:var connection_url: string containing the parameters to connect to the database.
Gets the values from :class:`app.config`
:var self.conn: psycopg2 connection object.
"""
connection_url = "dbname=%s user=%s password=%s host=%s port=%s" % (config.POSTGRES_DB,
config.POSTGRES_USER,
config.POSTGRES_PW,
config.POSTGRES_HOSTNAME,
config.POSTGRES_PORT)
self.conn = psycopg2._connect(connection_url)
|
"""
tests for the multiprocess
"""
from typing import Optional, Any, List
import pandas as pd
import pytest
import replicators.multiprocess as mult
TESTDATA = [pd.DataFrame(
columns=["This",
"is",
"a",
"test",
"to",
"check",
"a_function"],
data=[[5, 2, "b", 3, 4, 5, 3],
[7, 2, "b", 3, 4, 5, 3],
[8, 2, "b", 3, 4, 5, 3],
[3, 2, "b", 3, 4, 5, 3],
[2, 2, "b", 3, 4, 5, 3],
[8, 2, "b", 3, 4, 5, 3],
[2, 2, "b", 3, 4, 5, 3],
[8, 2, "b", 3, 4, 5, 3],
[19, 2, "b", 3, 4, 5, 3],
[53, 2, "b", 3, 4, 5, 3],
[11, 2, "b", 3, 4, 5, 3],
[16, 2, "b", 3, 4, 5, 3]])]
def return_this(anything: dict):
"""
returns the value in the "This" key.
:param anything:
:return:
"""
return anything["This"]
@pytest.mark.parametrize("data_frame", TESTDATA)
def test_multiprocess_me_side_effect(data_frame: pd.DataFrame):
"""
Used to test the multiprocess function without a return
"""
data: list = list(data_frame.T.to_dict().values())
mult.multiprocess_me(1, print, data, False)
@pytest.mark.parametrize("data_frame", TESTDATA)
def test_multiprocess_me_side_return(data_frame: pd.DataFrame):
"""
Used to test the multiprocess function without a return
"""
data: Optional[Any] = list(data_frame.T.to_dict().values())
got: Optional[List[Any]] = mult.multiprocess_me(1, return_this, data, True)
want: list = [5, 7, 8, 3, 2, 8, 2, 8, 19, 53, 11, 16]
assert got == want
def test_multiprocess_not_data_frame_input():
"""
Used to test the multiprocess function with a bad input
"""
data: str = "this is not a DataFrame"
try:
mult.multiprocess_me(1, print, data, False)
except mult.NotDict:
assert True
|
from django.db import models
from myutils.models import JSONField
from myutils.models import RichTextField
from myutils.constants import Choices
from account.models import User
from contest.models import Contest
# Create your models here.
class ProblemTag(models.Model):
name = models.TextField()
class Meta:
db_table = "problem_tag"
class ProblemRuleType(Choices):
ACM = "ACM"
OI = "OI"
class ProblemDifficulty(object):
High = "High"
Mid = "Mid"
Low = "Low"
class Problem(models.Model):
# 显示问题的ID
_id = models.TextField(db_index=True)
contest = models.ForeignKey(Contest,null=True)
# 对于比赛的问题来说
is_public = models.BooleanField(default=False)
title = models.TextField()
# Html 文本输入
description = RichTextField()
input_description = RichTextField()
output_description = RichTextField()
# [{input:"test",output:"123"},{input:"test123",output:"456"}]
samples = JSONField()
test_case_id = models.TextField()
# [{"input_name":"1.in","output_name":"1.out","score":0}]
# 测试用例的分数
test_case_score = JSONField()
hint = RichTextField(null=True)
languages = JSONField()
template = JSONField()
create_time = models.DateTimeField(auto_now_add=True)
# 对于最新的更新时间这里不能使用 auto_now
last_update_time = models.DateTimeField(null=True)
created_by = models.ForeignKey(User)
# ms(毫秒)
time_limit = models.IntegerField()
# MB
memory_limit = models.IntegerField()
# 下面的是与特殊评判相关的字段
spj = models.BooleanField(default=False)
spj_language = models.TextField(null=True)
spj_code = models.TextField(null=True)
spj_version = models.TextField(null=True)
spj_compile_ok = models.BooleanField(default=False)
rule_type = models.TextField()
visible = models.BooleanField(default=True)
difficulty = models.TextField()
# 问题的标签对应的是多对多的
tags = models.ManyToManyField(ProblemTag)
source = models.TextField(null=True)
# 对于OI 模式
total_score = models.IntegerField(default=0)
submission_number = models.BigIntegerField(default=0)
accepted_number = models.BigIntegerField(default=0)
# 对于提交之后该题目的统计信息，格式有ac和wa
# {JudgeStatus.ACCEPTED:3,JudgeStatus.WRONG_ANSWER:11},数字代表的是计数
statistic_info = JSONField(default=dict)
class Meta:
db_table = "problem"
unique_together = (("_id", "contest"),)
ordering = ("create_time",)
def add_submission_number(self):
# 增加提交的数目
self.submission_number = models.F("submission_number") + 1
self.save(update_fields=["submission_number"])
def add_ac_number(self):
# 计数器，每次ac一题，数目+1，增加通过的数目，当self.accepted_number=1时，是首次AC
self.accepted_number = models.F("accepted_number") + 1
self.save(update_fields=["accepted_number"])
|
from glob import glob
from PIL import Image
import numpy as np
import os
import pickle
def valid(path):
depth_path = path.replace('col', 'up_png')
depth_path = depth_path.replace('_c', '_ud')
exists = os.path.isfile(depth_path)
if not exists:
return False
return True
test_color_paths = glob(r'E:\test\**\col\*.png', recursive=True)
test_color_paths = [path for path in test_color_paths if valid(path)]
train_color_paths = glob(r'E:\train\**\col\*.png', recursive=True)
train_color_paths = [path for path in train_color_paths if valid(path)]
print("Found {} valid train files".format(len(train_color_paths)))
print("Found {} valid test files".format(len(test_color_paths)))
train_f = open('train_color_paths.obj', 'wb')
pickle.dump(train_color_paths, train_f)
train_f.close()
test_f = open('test_color_paths.obj', 'wb')
pickle.dump(test_color_paths, test_f)
test_f.close()
|
# Generated by Django 3.2 on 2021-08-22 15:15
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('authors', '0003_author_middlename'),
]
operations = [
migrations.AddField(
model_name='author',
name='image',
field=models.ImageField(default='default.jpg', upload_to='author_pics'),
),
]
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.conf.urls import url
from .views import (
CreateAlbumView, AlbumsListView, AlbumImagesView, AlbumImportView,
)
urlpatterns = [
url(r'^$', AlbumsListView.as_view(),
name='album-list'),
url(r'^album/create/', CreateAlbumView.as_view(),
name='album-create'),
url(r'^album/(?P<album_name>[a-zA-Z]+)/$', AlbumImagesView.as_view(),
name='album-detail'),
url(r'^album/(?P<album_name>[a-zA-Z]+)/import/$', AlbumImportView.as_view(),
name='album-import-photos'),
]
|
#!/usr/bin/env /proj/sot/ska/bin/python
#################################################################################################
# #
# acis_cti_trend_dom.py: computing trend line with dom #
# #
# author: t. isobe (tisobe@cfa.harvard.edu) #
# #
# Last update: Jun 16, 2014 #
# #
#################################################################################################
import os
import sys
import re
import string
import random
import operator
import numpy
import math
#
#--- check whether this is a test case
#
comp_test = 'live'
if len(sys.argv) == 2:
if sys.argv[1] == 'test': #---- test case
comp_test = 'test'
elif sys.argv[1] == 'live': #---- automated read in
comp_test = 'live'
else:
comp_test = sys.argv[1].strip() #---- input data name
#
#--- reading directory list
#
if comp_test == 'test' or comp_test == 'test2':
path = '/data/mta/Script/ACIS/CTI/house_keeping/dir_list_py_test'
else:
path = '/data/mta/Script/ACIS/CTI/house_keeping/dir_list_py'
f = open(path, 'r')
data = [line.strip() for line in f.readlines()]
f.close()
for ent in data:
atemp = re.split(':', ent)
var = atemp[1].strip()
line = atemp[0].strip()
exec "%s = %s" %(var, line)
#
#--- append a path to a private folder to python directory
#
sys.path.append(bin_dir)
sys.path.append(mta_dir)
#
#--- converTimeFormat contains MTA time conversion routines
#
import convertTimeFormat as tcnv
import mta_common_functions as mcf
import robust_linear as robust #---- robust linear fit
from kapteyn import kmpfit
#import kmpfit_chauvenet as chauv
#
#--- temp writing file name
#
rtail = int(10000 * random.random())
zspace = '/tmp/zspace' + str(rtail)
#
#--- set several lists
#
dir_set = ['Data2000', 'Data119', 'Data7000', 'Data_adjust', 'Data_cat_adjust']
det_set = ['Det_Data2000', 'Det_Data119', 'Det_Data7000', 'Det_Data_adjust', 'Det_Data_cat_adjust']
out_set = ['Plot2000', 'Plot119', 'Plot7000', 'Plot_adjust', 'Plot_cat_adjust']
dout_set = ['Det_Plot2000', 'Det_Plot119', 'Det_Plot7000', 'Det_Plot_adjust', 'Det_Plot_cat_adjust']
elm_set = ['al', 'mn', 'ti']
#---------------------------------------------------------------------------------------------------
#-- fit_line_with_dom: plot indivisual CCD CTI trends and combined CTI trends for all different cases --
#---------------------------------------------------------------------------------------------------
def fit_line_with_dom(indirs, outdirs, allccd = 1):
"""
plot indivisual CCD CTI trends and combined CTI trends for all different cases
Input: indirs --- a list of directories which contain data
outdirs --- a list of directories which the plots will be deposted
allccd --- if it is 1, the funciton processes all ccd, if it is 0, detrended ccd only
Output: plots such as <elm>_ccd<ccd#>_plot.png, imaging_<elm>_plot.png, etc
fitting_result --- a file contains a table of fitted parameters
combined data sets such as imging_<elm>_comb, spectral_<elm>_comb etc saved in data_dir/<indir>
"""
if allccd == 0: #--- detrended data case
ccd_list = [0, 1, 2, 3, 4, 6, 8, 9]
else:
ccd_list = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] #---- normal case
xname = 'Time (Year)'
yname = '(S/I)x10**4'
for k in range(0, len(indirs)):
dir = indirs[k]
# file = data_dir + dir + '/fitting_result'
file = web_dir + outdirs[k] + '/fitting_result_dom'
fo = open(file, 'w')
for elm in elm_set:
uelm = elm
uelm.lower()
line = '\n\n' + uelm + ' K alpha' + '\n'
fo.write(line)
#
#--- write a table head
#
fo.write('----------\n')
fo.write('CCD Quad0 Quad1 Quad2 Quad3\n')
fo.write(' Slope Sigma Slope Sigma Slope Sigma Slope Sigma\n\n')
#
#--- read each ccd data set
#
for ccd in ccd_list:
file = data_dir + dir + '/' + elm + '_ccd' + str(ccd)
f = open(file, 'r')
data = [line.strip() for line in f.readlines()]
f.close()
#
#--- fit a line and get intercepts and slopes: they are save in a list form
#
(xSets, ySets, yErrs) = rearrangeData(data)
(intList, slopeList, serrList) = fitLines(xSets, ySets)
line = str(ccd) + '\t'
fo.write(line)
entLabels = []
for i in range(0, 4):
#
#--- create a title label for plot
#
line = 'CCD' + str(ccd) + ': Node' + str(i)
entLabels.append(line)
#
#--- print out the slope and the error for each quad
#
line = "%3e\t%3e\t" % (slopeList[i], serrList[i])
fo.write(line)
fo.write('\n')
#
#--- create combined plots (image ccd, spec ccd, backside ccds)
#
sccd_list = [0, 1, 2, 3]
(newX, newY, newE, intc, slope, serr) = compute_fitting(elm, sccd_list, 'imaging', indirs[k], outdirs[k])
fo.write('ACIS-I Average: ')
line = "%3e\t%3e\n" % (slope, serr)
fo.write(line)
sccd_list = [4, 6, 7, 9]
(newX, newY, newE, intc, slope, serr) = compute_fitting(elm, sccd_list, 'spectral', indirs[k], outdirs[k])
fo.write('ACIS-S Average w/o BI: ')
line = "%3e\t%3e\n" % (slope, serr)
fo.write(line)
if allccd == 1:
sccd_list = [5]
(newX, newY, newE, intc, slope, serr) = compute_fitting(elm, sccd_list, 'backside_5', indirs[k], outdirs[k])
fo.write('Back Side CCD 5: ')
line = "%3e\t%3e\n" % (slope, serr)
fo.write(line)
sccd_list = [7]
(newX, newY, newE, intc, slope, serr) = compute_fitting(elm, sccd_list, 'backside_7', indirs[k], outdirs[k])
fo.write('Back Side CCD 7: ')
line = "%3e\t%3e\n" % (slope, serr)
fo.write(line)
fo.close()
#---------------------------------------------------------------------------------------------------
#-- compute_fitting: create combined data set to prepare for the plot --
#---------------------------------------------------------------------------------------------------
def compute_fitting(elm, ccd_list, head, indir, outdir):
"""
create combined data set to prepare for the plot
Input: elm --- element
ccd_list--- a list of ccd to be used
head --- a header for the plot/data table
indir --- a directory where the data is kept
outdir --- a directory where the plot will be deposted
Output: a list of
newX --- combined X values in a list
newY --- combined Y values in a list
newE --- combined Error of Y
intList[0] --- intercept
slopeList[0]--- slope
serrList[0] --- erorr of the slope
data such as imaging_<elm>_comb this is kept in <indir>
"""
#
#
comb_data = []
for ccd in ccd_list:
file = data_dir + indir +'/' + elm + '_ccd' + str(ccd)
f = open(file, 'r')
data = [line.strip() for line in f.readlines()]
f.close()
comb_data = comb_data + data
#
#--- separate the data into each node
#
(xSets, ySets, yErrs) = rearrangeData(comb_data)
xlist = numpy.array(xSets[0])
qlist = [[] for x in range(0, 4)]
elist = [[] for x in range(0, 4)]
qsorted = [[] for x in range(0, 4)]
esorted = [[] for x in range(0, 4)]
for i in range(0, 4):
qlist[i] = numpy.array(ySets[i])
elist[i] = numpy.array(yErrs[i])
order = numpy.argsort(xlist)
xsorted = xlist[order]
for i in range(0, 4):
qsorted[i] = qlist[i][order]
esorted[i] = elist[i][order]
#
#--- print out combined data
#
file = data_dir + indir + '/' + head + '_' + elm + '_comb'
fp = open(file, 'w')
newX = []
newY = []
newE = []
yVar = []
eVar = []
start = 0
stop = 30
for i in range(0, len(xsorted)):
x = xsorted[i]
if (x >= start) and (x < stop):
for j in range(0, 4):
yVar.append(qsorted[j][i])
eVar.append(esorted[j][i])
else:
tcnt = 0
sum = 0
sum1 = 0
sum2 = 0
esum = 0
for k in range(0, len(yVar)):
#
#--- remove -99999 error
#
if yVar[k] > 0.0:
err2 = (1/eVar[k]) * (1/eVar[k])
var = yVar[k] * err2
sum += var
sum1 += yVar[k]
sum2 += yVar[k] * yVar[k]
esum += err2
tcnt += 1
if tcnt > 0:
meanv = sum / esum
sigma = math.sqrt(1.0 / sum2)
# avg = sum1 / tcnt
# sigma = math.sqrt(sum2 / tcnt - avg * avg)
mid = int(0.5 * (start + stop))
newX.append(mid)
newY.append(meanv)
newE.append(sigma)
line = str(mid) + '\t' + str(meanv) + '\t' + str(sigma) + '\n'
fp.write(line)
start = stop
stop = start + 30
yVar = []
eVar = []
for j in range(0, 4):
yVar.append(qsorted[j][i])
eVar.append(esorted[j][i])
fp.close()
#
#--- since fitLines takes only a list of lists, put in a list
#
XSets = [newX]
YSets = [newY]
#
#--- find a fitting line parameters
#
(intList, slopeList, serrList) = fitLines(xSets, ySets)
#
#--- set Y plot range
#
ypositive = []
for ent in newY:
if ent > 0:
ypositive.append(ent)
return (newX, newY, newE, intList[0], slopeList[0], serrList[0])
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
def fyear_to_dom(dlist):
dom_list = []
for ent in dlist:
year = int(ent)
fy = ent - year
if tcnv.isLeapYear(year) == 1:
base = 366
else:
base = 365
ydate = int(base * fy)
dom = tcnv.YdateToDOM(year, ydate)
dom_list.append(dom)
return dom_list
#---------------------------------------------------------------------------------------------------
#-- isolateData: separate a table data into arrays of data ---
#---------------------------------------------------------------------------------------------------
def isolateData(ccd, elm, quad, dir_set):
"""
separate a table data into arrays of data
Input: ccd --- ccd #
elm --- name of element
quad --- quad #
dir_set --- a list of data directories
Output: xSets --- a list of lists of x values in fractional year
ySets --- a list of lists of y values
"""
xSets = []
ySets = []
eSets = []
for dir in dir_set:
file = data_dir + dir + '/' + elm + '_ccd' + str(ccd)
f = open(file, 'r')
data = [line.strip() for line in f.readlines()]
f.close()
#
#--- separeate a table into each column array
#
coldata = mcf.separate_data_to_arrys(data)
#
#--- convert time into dom ( xxxfractional year) (a list of time)
#
time = convTimeFullColumn2(coldata[0])
xSets.append(time)
tmax = max(time)
#
#--- the data part come with cti +- error. drop the error part
#
[ydata, yerr] = separateErrPart(coldata[quad + 1])
ySets.append(ydata)
eSets.append(yerr)
#
#--- round the data accuracy to 0.1
#
ypositive = []
for ent in ydata:
if ent > 0:
ypositive.append(ent)
return [ xSets, ySets, eSets]
#---------------------------------------------------------------------------------------------------
#-- rearrangeData: separate a table data into time and 4 quad data array data sets --
#---------------------------------------------------------------------------------------------------
def rearrangeData(data):
"""
separate a table data into time and 4 quad data array data sets
Input: data --- input table data
Output: xSets --- a list of lists of x values
ySets --- a list of lists of y values
yErrs --- a list of lists of y errors
"""
xSets = []
ySets = []
yErrs = []
coldata = mcf.separate_data_to_arrys(data)
time = convTimeFullColumn(coldata[0]) #---- time in fractional year
time2 = convTimeFullColumn2(coldata[0]) #---- time in dom
#
#--- go around each quad data
#
for i in range(1, 5):
xSets.append(time2)
data = []
error = []
for ent in coldata[i]:
atemp = re.split('\+\-', ent)
data.append(float(atemp[0]))
error.append(float(atemp[1]))
ySets.append(data)
yErrs.append(error)
ypositive = []
for ent in data:
if ent > 0:
ypositive.append(ent)
return (xSets, ySets, yErrs)
#---------------------------------------------------------------------------------------------------
#-- fitLines: find intercepts and slopes of sets of x and y values --
#---------------------------------------------------------------------------------------------------
def fitLines(xSets, ySets, echk = 1):
"""
find intercepts and slopes of sets of x and y values
Input: xSets --- a list of independent variable lists
ySets --- a list of dependent variable lists
echk --- if it is larger than 0, compute slope error (default: 1)
Output: inList --- a list of intercepts
slopeList--- a list of slopes
serrlist--- a list of slope errors
"""
intList = []
slopeList = []
serrList = []
for i in range(0, len(xSets)):
[intc, slope, ierr, serr] = linear_fit(xSets[i], ySets[i])
intList.append(intc)
slopeList.append(slope)
serrList.append(serr)
return (intList, slopeList, serrList)
#---------------------------------------------------------------------------------------------------
#-- linear_fit: linear fitting function with 99999 error removal ---
#---------------------------------------------------------------------------------------------------
def linear_fit(x, y):
"""
linear fitting function with -99999 error removal
Input: x --- independent variable array
y --- dependent variable array
Output: intc --- intercept
slope--- slope
"""
#
#--- first remove error entries
#
sum = 0
sum2 = 0
tot = 0
for i in range(0, len(y)):
if y[i] > 0:
sum += y[i]
sum2 += y[i] *y[i]
tot += 1
if tot > 0:
avg = sum / tot
sig = math.sqrt(sum2/tot - avg * avg)
else:
avg = 3.0
lower = 0.0
upper = avg + 2.0
xn = []
yn = []
for i in range(0, len(x)):
if (y[i] > lower) and (y[i] < upper):
xn.append(x[i])
yn.append(y[i])
if len(yn) > 10:
[intc, slope, serr] = robust.robust_fit(xn, yn, iter=50)
else:
[intc, slope, serr] = [0, 0, 0]
return [intc, slope, 0.0, serr]
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
def model(p, x):
a, b = p
y = a + b * x
return y
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
def residuals(p, data):
x, y = data
return y - model(p, x)
#---------------------------------------------------------------------------------------------------
#-- convTimeFullColumn: convert time format to fractional year for the entire array ---
def convTimeFullColumn(time_list):
"""
convert time format to fractional year for the entire array
Input: time_list --- a list of time
Output: converted --- a list of tine in fractional year
"""
converted = []
for ent in time_list:
time = tcnv.dateFormatConAll(ent)
year = time[0]
ydate = time[6]
chk = 4.0 * int(0.25 * year)
if year == chk:
base = 366
else:
base = 365
yf = year + ydate / base
converted.append(yf)
return converted
#---------------------------------------------------------------------------------------------------
#-- convTimeFullColumn2: convert time format to dom for the entire array ---
#---------------------------------------------------------------------------------------------------
def convTimeFullColumn2(time_list):
"""
convert time format to fractional year for the entire array
Input: time_list --- a list of time
Output: converted --- a list of tine in dom
"""
converted = []
for ent in time_list:
time = tcnv.dateFormatConAll(ent)
year = time[0]
ydate = time[6]
dom = tcnv.YdateToDOM(year, ydate)
converted.append(dom)
return converted
#---------------------------------------------------------------------------------------------------
#-- separateErrPart: separate the error part of each entry of the data array ---
#---------------------------------------------------------------------------------------------------
def separateErrPart(data):
"""
drop the error part of each entry of the data array
Input: data --- data array
Ouptput:cleane --- data array without error part
err --- data array of error
"""
cleaned = []
err = []
for ent in data:
atemp = re.split('\+\-', ent)
cleaned.append(float(atemp[0]))
err.append(float(atemp[1]))
return [cleaned,err]
#--------------------------------------------------------------------------------------------------
if __name__ == '__main__':
fit_line_with_dom(dir_set, out_set)
fit_line_with_dom(det_set, dout_set, allccd = 0)
|
# Using curl or similarr provide a script that monitors the stub_status endpoint created in the Nginx section. Can you parse the "Active connections" and get the value?
import requests
response = requests.get('http://localhost/basic_status')
# [0] to get the first line [1] to get the second part of the string after the ":" character and [1:] to remove the space before the number
active_connections = response.text.splitlines()[0].split(":")[1][1:]
print(active_connections)
|
import numpy as np
import cv2
from matplotlib import pyplot as plt
def open(img):
cv2.imshow('d',img)
cv2.waitKey(0 )
cv2.destroyAllWindows()
img = cv2.imread('digits.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# Now we split the image to 5000 cells, each 20x20 size
cells = [np.hsplit(row,100) for row in np.vsplit(gray,50)]
# Make it into a Numpy array. It size will be (50,100,20,20)
x = np.array(cells)
l = 0
for i in x:
for j in i:
cv2.imwrite(r'D:\Github_project\OPENCV\Test\lol\{0}.png'.format(str(l)),j)
l+=1
# Now we prepare train_data and test_data.
train = x[:,:10].reshape(-1,400).astype(np.float32) # Size = (2500,400)
test = x[:,50:90].reshape(-1,400).astype(np.float32) # Size = (2500,400)
# for i in test:
# cv2.imwrite(r'D:\Github_project\OPENCV\Test\lol\rt.png', img)
# # Create labels for train and test data
k = np.arange(10)
train_labels = np.repeat(k,50)[:,np.newaxis]
test_labels = np.repeat(k,200)[:,np.newaxis]
im = cv2.imread(r'D:\Github_project\OPENCV\Test\lol\60.png')
arr = np.array(train[0])
ter = arr.reshape(-1,400).astype(np.float32)
open(ter)
# # Initiate kNN, train the data, then test it with test data for k=1
knn = cv2.ml.KNearest_create()
knn.train(train,cv2.ml.ROW_SAMPLE,train_labels)
ret,result,neighbours,dist = knn.findNearest(test,k=1)
print(ret)
# print(result)
# # Now we check the accuracy of classification
# # For that, compare the result with test_labels and check which are wrong
matches = result==test_labels
# print(matches)
correct = np.count_nonzero(matches)
# print(correct)
accuracy = correct*100.0/result.size
print (accuracy)
|
from os.path import dirname, realpath, exists
import ctypes
import sys
import os
import math
import logging
import pprint
import random
class UControllersError(Exception):
def __init__(self, message, ucontroller_name=""):
super().__init__(message)
self.ucontroller_name = ucontroller_name
class UControllers:
def __init__(self, emulate=False):
self.ucontrollers_lib = None
self.logger = logging.getLogger(self.__class__.__name__)
self.emulate = emulate
lib_path = dirname(realpath(__file__)) + '/ucontrollers'
# Check if 32 or 64 bit
if sys.maxsize <= 2**32:
lib_path += '32'
else:
lib_path += '64'
# Check OS
if os.name == 'posix':
lib_path += '.so'
elif os.name == 'nt':
lib_path += '.dll'
if exists(lib_path):
self.ucontrollers_lib = ctypes.cdll.LoadLibrary(lib_path)
else:
error = "Unsupported platform."
self.logger.error(error)
raise UControllersError(error)
if self.ucontrollers_lib == None:
error = "Could not load the microcontrollers lib."
self.logger.error(error)
raise UControllersError(error)
self.ucontrollers_lib.init.restype = ctypes.c_char_p
self.ucontrollers_lib.end.restype = ctypes.c_char_p
self.ucontrollers_lib.get_ucontroller_count.restype = ctypes.c_int
self.ucontrollers_lib.send_cmd.argtypes = (ctypes.c_uint, ctypes.c_int)
self.ucontrollers_lib.send_cmd.restype = ctypes.c_char_p
if self.emulate:
self.logger.debug("Emulated microcontrollers connected.")
else:
self.logger.info("Searching for microcontrollers...")
self._process_output(self.ucontrollers_lib.init())
count = self.ucontrollers_lib.get_ucontroller_count()
self.logger.info("Found {} microcontroller(s).".format(count))
def get_ucontroller_count(self):
if self.emulate:
return 2
else:
return self.ucontrollers_lib.get_ucontroller_count()
def daynight_inform(self, is_night):
if is_night:
if not self.emulate:
for i in range(self.ucontrollers_lib.get_ucontroller_count()):
self._process_output(self.ucontrollers_lib.send_cmd(i, 0))
self.logger.info("Microcontrollers informed of night approaching.")
else:
if not self.emulate:
for i in range(self.ucontrollers_lib.get_ucontroller_count()):
self._process_output(self.ucontrollers_lib.send_cmd(i, 1))
self.logger.info("Microcontrollers informed of day approaching.")
def get_measurements_list(self):
measurements_list = []
if self.emulate:
for i in range(1, 3):
measurements = { 'name' : 'Emulated ' + str(i), 'data' : {
'Temperature' : str(random.uniform(20, 40)) + 'C',
'Humidity' : str(random.uniform(30, 90)) + '%',
'Camera voltage' : str(random.uniform(11, 13)) + 'V',
'PSU' : 'on' if random.random() < 0.5 else 'off'
}
}
measurements_list.append(measurements)
else:
for i in range(self.ucontrollers_lib.get_ucontroller_count()):
measurements = {}
output = self._process_output(self.ucontrollers_lib.send_cmd(i, 2))
measurements['name'] = output.split('\n')[1]
output = self._process_output(self.ucontrollers_lib.send_cmd(i, 3), measurements['name'])
measurements['data'] = {}
for line in output.split('\n')[1:]:
if line.strip() == "": continue
key, value = line.split(':')
measurements['data'][key] = value
measurements_list.append(measurements)
same_names = {}
for name_data in measurements_list:
name = name_data['name']
if name in same_names:
current_count = same_names[name][1]
if current_count == 1: same_names[name][0]['name'] += " ({})".format(current_count)
name_data['name'] += " ({})".format(current_count + 1)
same_names[name] = (name_data, current_count + 1)
else:
same_names[name] = (name_data, 1)
self.logger.info("Measurements received:\n" + pprint.pformat(measurements_list))
return measurements_list
def _process_output(self, output, ucontroller_name=""):
output = output.decode('utf-8')
if "ERROR: " in output:
error = output.replace("ERROR: ", "")
self.logger.error(error)
raise UControllersError(error, ucontroller_name)
elif "INFO: " in output:
self.logger.info(output.replace("INFO: ", ""))
elif "DEBUG: " in output:
self.logger.debug(output.replace("DEBUG: ", ""))
return output
def end(self):
if self.emulate:
self.logger.debug("Emulated microcontrollers disconnected.")
else:
self._process_output(self.ucontrollers_lib.end())
def __enter__(self):
return self
def __exit__(self, exc_type, exc_value, traceback):
self.end()
|
a = 26
b= 11.3
c=5
d= 3.5
#suma
print a," +",b,"=", a+b
#resta
print b," +",a,"=",c-a
#multiplicacion
print d,"*",a ,"=" ,d*a
#exponente
print c,"^",2 ,"=",c**2
#division
print c,"/",2 ,"=",c/2
#division ...
print float(c),"/",2 ,"=", float(c)/2
#modulo ...
print 7,"%",3 ,"=", 7%3
|
Python 3.4.3 (v3.4.3:9b73f1c3e601, Feb 24 2015, 22:44:40) [MSC v.1600 64 bit (AMD64)] on win32
Type "copyright", "credits" or "license()" for more information.
>>> print("hello")
hello
>>> print('hello')
hello
>>> a="hello"
>>> print(a)
hello
>>> a = """Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.
It is used for:
web development (server-side),
software development,
mathematics,
system scripting."""
>>> print(a)
Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.
It is used for:
web development (server-side),
software development,
mathematics,
system scripting.
>>> a="hello ,word"
>>> print(a[1])
e
>>> b="hello ,word"
>>> print(b[2:5])
llo
>>>
|
# @Time :2019/7/13 0:15
# @Author :jinbiao
|
#encoding: utf-8
edad=100
if edad >= 0 and edad < 18:
print "eres un niño"
elif edad >= 18 and edad < 27:
print "eres un joven"
elif edad>= 27 and 60 >edad:
print "eres adulto"
else:
print "eres de la tercera edad"
|
import unittest
#suite = unittest.TestLoader().loadTestsFromModule(test)
#unittest.TextTestRunner(verbosity=2).run(suite)
if __name__ == '__main__':
unittest.main()
|
#!/usr/bin/env python
"""This script subscribes to a topic and logs the ExampleMessage objects read"""
import rospy
from example.msg import ExampleMessage
NODE_NAME = 'topic_subscriber'
TOPIC_NAME = 'topic'
def topic_callback(data):
rospy.loginfo('{} - {}'.format(
rospy.get_caller_id(),
data
))
def run():
rospy.init_node(NODE_NAME)
_ = rospy.Subscriber(TOPIC_NAME, ExampleMessage, topic_callback)
rospy.spin()
if __name__ == '__main__':
try:
run()
except rospy.ROSInterruptException:
pass
|
#!/usr/bin/env python3
# Copyright (c) 2012, the Dart project authors. Please see the AUTHORS file
# for details. All rights reserved. Use of this source code is governed by a
# BSD-style license that can be found in the LICENSE file.
"""This module generates Dart APIs from the IDL database."""
import emitter
import idlnode
import logging
import os
import re
import shutil
from generator import *
from idlnode import IDLType, IDLInterface, resolveTypedef
_logger = logging.getLogger('dartgenerator')
def MergeNodes(node, other):
node.operations.extend(other.operations)
for attribute in other.attributes:
if not node.has_attribute(attribute):
node.attributes.append(attribute)
node.constants.extend(other.constants)
class DartGenerator(object):
"""Utilities to generate Dart APIs and corresponding JavaScript."""
def __init__(self, logging_level=logging.WARNING):
self._auxiliary_files = {}
self._dart_templates_re = re.compile(r'[\w.:]+<([\w \.<>:]+)>')
_logger.setLevel(logging_level)
def _StripModules(self, type_name):
return type_name.split('::')[-1]
def _IsCompoundType(self, database, type_name):
if IsRegisteredType(type_name):
return True
# References a typedef - normally a union type.
if database.HasTypeDef(type_name):
return True
if type_name.endswith('?'):
return self._IsCompoundType(database, type_name[:-len('?')])
if type_name.endswith('[]'):
return self._IsCompoundType(database, type_name[:-len('[]')])
stripped_type_name = self._StripModules(type_name)
if (database.HasInterface(stripped_type_name) or
database.HasDictionary(stripped_type_name)):
return True
if database.HasEnum(stripped_type_name):
return True
dart_template_match = self._dart_templates_re.match(type_name)
if dart_template_match:
# Dart templates
parent_type_name = type_name[0:dart_template_match.start(1) - 1]
sub_type_name = dart_template_match.group(1)
return (self._IsCompoundType(database, parent_type_name) and
self._IsCompoundType(database, sub_type_name))
return False
def _IsDartType(self, type_name):
return '.' in type_name
def LoadAuxiliary(self, auxiliary_dir):
for (dirname, _, names) in os.walk(auxiliary_dir):
for name in names:
if name.endswith('.dart'):
name = name[0:-5] # strip off ".dart"
self._auxiliary_files[name] = os.path.join(dirname, name)
def FilterMembersWithUnidentifiedTypes(self, database):
"""Removes unidentified types.
Removes constants, attributes, operations and parents with unidentified
types.
"""
for interface in database.GetInterfaces():
def IsIdentified(idl_node):
node_name = idl_node.id if idl_node.id else 'parent'
for idl_type in idl_node.all(idlnode.IDLType):
type_name = idl_type.id
if (type_name is not None and
self._IsCompoundType(database, type_name)):
continue
# Ignore constructor warnings.
if not (interface.id in [
'Window', 'WorkerContext', 'WorkerGlobalScope'
] and type_name.endswith('Constructor')):
_logger.warn(
'removing %s in %s which has unidentified type %s' %
(node_name, interface.id, type_name))
return False
return True
interface.constants = list(filter(IsIdentified,
interface.constants))
interface.attributes = list(
filter(IsIdentified, interface.attributes))
interface.operations = list(
filter(IsIdentified, interface.operations))
interface.parents = list(filter(IsIdentified, interface.parents))
def FilterInterfaces(self,
database,
and_annotations=[],
or_annotations=[],
exclude_displaced=[],
exclude_suppressed=[]):
"""Filters a database to remove interfaces and members that are missing
annotations.
The FremontCut IDLs use annotations to specify implementation
status in various platforms. For example, if a member is annotated
with @WebKit, this means that the member is supported by WebKit.
Args:
database -- the database to filter
all_annotations -- a list of annotation names a member has to
have or it will be filtered.
or_annotations -- if a member has one of these annotations, it
won't be filtered even if it is missing some of the
all_annotations.
exclude_displaced -- if a member has this annotation and it
is marked as displaced it will always be filtered.
exclude_suppressed -- if a member has this annotation and it
is marked as suppressed it will always be filtered.
"""
# Filter interfaces and members whose annotations don't match.
for interface in database.GetInterfaces():
def HasAnnotations(idl_node):
"""Utility for determining if an IDLNode has all
the required annotations"""
for a in exclude_displaced:
if (a in idl_node.annotations and
'via' in idl_node.annotations[a]):
return False
for a in exclude_suppressed:
if (a in idl_node.annotations and
'suppressed' in idl_node.annotations[a]):
return False
for a in or_annotations:
if a in idl_node.annotations:
return True
if and_annotations == []:
return False
for a in and_annotations:
if a not in idl_node.annotations:
return False
return True
if HasAnnotations(interface):
interface.constants = filter(HasAnnotations,
interface.constants)
interface.attributes = filter(HasAnnotations,
interface.attributes)
interface.operations = filter(HasAnnotations,
interface.operations)
interface.parents = filter(HasAnnotations, interface.parents)
else:
database.DeleteInterface(interface.id)
self.FilterMembersWithUnidentifiedTypes(database)
def Generate(self, database, super_database, generate_interface):
self._database = database
# Collect interfaces
interfaces = []
for interface in database.GetInterfaces():
if not MatchSourceFilter(interface):
# Skip this interface since it's not present in the required source
_logger.info('Omitting interface - %s' % interface.id)
continue
interfaces.append(interface)
# All web_gl constants from WebGLRenderingContextBase, WebGL2RenderingContextBase, WebGLDrawBuffers are generated
# in a synthesized class WebGL. Those IDLConstants are in web_gl_constants.
web_gl_constants = []
# Render all interfaces into Dart and save them in files.
for interface in self._PreOrderInterfaces(interfaces):
interface_name = interface.id
auxiliary_file = self._auxiliary_files.get(interface_name)
if auxiliary_file is not None:
_logger.info('Skipping %s because %s exists' % (interface_name,
auxiliary_file))
continue
_logger.info('Generating %s' % interface.id)
generate_interface(interface, gl_constants=web_gl_constants)
# Generate the WEB_GL constants
web_gl_constants_interface = IDLInterface(None, "WebGL")
web_gl_constants_interface.constants = web_gl_constants
self._database._all_interfaces['WebGL'] = web_gl_constants_interface
generate_interface(web_gl_constants_interface)
def _PreOrderInterfaces(self, interfaces):
"""Returns the interfaces in pre-order, i.e. parents first."""
seen = set()
ordered = []
def visit(interface):
if interface.id in seen:
return
seen.add(interface.id)
for parent in interface.parents:
if IsDartCollectionType(parent.type.id):
continue
if self._database.HasInterface(parent.type.id):
parent_interface = self._database.GetInterface(
parent.type.id)
visit(parent_interface)
ordered.append(interface)
for interface in interfaces:
visit(interface)
return ordered
def IsEventTarget(self, database, interface):
if interface.id == 'EventTarget':
return True
for parent in interface.parents:
parent_name = parent.type.id
if database.HasInterface(parent_name):
parent_interface = database.GetInterface(parent.type.id)
if self.IsEventTarget(database, parent_interface):
return True
return False
def FixEventTargets(self, database):
for interface in database.GetInterfaces():
if self.IsEventTarget(database, interface):
# Add as an attribute for easy querying in generation code.
interface.ext_attrs['EventTarget'] = None
elif 'EventTarget' in interface.ext_attrs:
# Create fake EventTarget parent interface for interfaces that have
# 'EventTarget' extended attribute.
ast = [('Annotation', [('Id', 'WebKit')]),
('InterfaceType', ('ScopedName', 'EventTarget'))]
interface.parents.append(idlnode.IDLParentInterface(ast))
def AddMissingArguments(self, database):
ARG = idlnode.IDLArgument([('Type', ('ScopedName', 'object')),
('Id', 'arg')])
for interface in database.GetInterfaces():
for operation in interface.operations:
call_with = operation.ext_attrs.get('CallWith', [])
if not (isinstance(call_with, list)):
call_with = [call_with]
constructor_with = operation.ext_attrs.get(
'ConstructorCallWith', [])
if not (isinstance(constructor_with, list)):
constructor_with = [constructor_with]
call_with = call_with + constructor_with
if 'ScriptArguments' in call_with:
operation.arguments.append(ARG)
def CleanupOperationArguments(self, database):
for interface in database.GetInterfaces():
for operation in interface.operations:
# TODO(terry): Hack to remove 3rd arguments in setInterval/setTimeout.
if ((operation.id == 'setInterval' or operation.id == 'setTimeout') and \
operation.arguments[0].type.id == 'any'):
operation.arguments.pop(2)
# Massage any operation argument type that is IDLEnum to String.
for index, argument in enumerate(operation.arguments):
type_name = argument.type.id
if database.HasEnum(type_name):
operation.arguments[index].type = IDLType('DOMString')
|
from Tested_Method.MethodToTest import Add
def test_Add_2_and_2_return_4():
#given
x = 2
y = 2
#when
result = Add(x,y)
#then
assert result == 4
|
class Camera:
def __init__(self, brand, model, price, format):
self.brand = brand
self.model = model
self.price = price
self.setFormat(format)
def getBrand(self):
return self.brand
def getModel(self):
return self.model
def getPrice(self):
return self.price
def getFormat(self):
return self.format
def setBrand(self,n_brand):
self.brand = n_brand
def setModel(self,n_model):
self.model = n_model
def setPrice(self, n_price):
self.price = n_price
def setFormat(self, n_format):
if n_format == 135 or n_format == 120:
self.format = n_format
else:
self.format = "해당 없음"
|
print("Arecursive program........")
def fun(val):
#if val <=1:
if (val == 0):
return 1
#print (val,end = " ")
fun(val - 1)
print (val, end = " ")
def main():
no = int(input("Enter number:"))
fun(no)
if __name__ == "__main__":
main()
|
from random import randrange as rnd, choice
import tkinter as tk
from tkinter import*
import math
import time
root = tk.Tk()
root.geometry('885x558')
cosmos=Canvas(root, width=885,height=558,)
fon = PhotoImage(file="cosmos.png")
id_img= cosmos.create_image(0,0,anchor=NW,image=fon)
cosmos.pack()
angle=0
class planet():
def __init__(self):
self.id = cosmos.create_oval(0,0,0,0)
self.live=1
def solnce(self):
x=self.x=0
y=self.y=558
r=self.r=125
color=self.color="yellow"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def mercury(self):
x=self.x=0
y=self.y=558
r=self.r=20
self.xn=0 # !!!начало координат!!!
self.yn=558 #!!! начало координат!!!
self.rv=165 #!!! собственный радиус вращения!!!
self.v=+1.0 # !!! скорость поворота
color=self.color="white"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def venera(self):
x=self.x=0
y=self.y=558
r=self.r=30
self.xn=0
self.yn=558
self.rv=225
self.v=-2.2
color=self.color="grey"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def earth(self):
x=self.x=0
y=self.y=558
r=self.r=40
self.xn=0
self.yn=558
self.rv=295
self.v=-4.3
color=self.color="blue"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def mars(self):
x=self.x=342
y=self.y=279
r=self.r=30
self.xn=0
self.yn=558
self.rv=370
self.v=-4.0
color=self.color="red"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
cosmos.itemconfig(self.id, fill=color)
def jupiter(self):
x=self.x=342
y=self.y=279
r=self.r=60
self.xn=0
self.yn=558
self.rv=460
self.v=-6.4
color=self.color="pink"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def saturn(self):
x=self.x=342
y=self.y=279
r=self.r=50
self.xn=0
self.yn=558
self.rv=560
self.v=-5.6
color=self.color="sky blue"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def uran (self):
x=self.x=342
y=self.y=279
r=self.r=40
self.xn=0
self.yn=558
self.rv=650
self.v=-3.3
color=self.color="deep sky blue"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def neptun(self):
x=self.x=342
y=self.y=279
r=self.r=40
self.xn=0
self.yn=558
self.rv=700
self.v=0
color=self.color="medium blue"
cosmos.coords(self.id, x-r, y-r, x+r, y+r)
cosmos.itemconfig(self.id, fill=color)
def set_coords(self):
cosmos.coords(
self.id,
self.x - self.r,
self.y - self.r,
self.x + self.r,
self.y + self.r
)
def move(self):
global angle
angle+=0.02
if angle>=360:
angle=0
self.x =self.xn+ self.rv* math.sin(angle-self.v)
self.y =self.yn+ self.rv* math.cos(angle-self.v)
self.set_coords()
def focIn(self,event):
print('Focus')
cosmos.itemconfig(self.id,fill='white')
t1=planet()
t2=planet()
t3=planet()
t4=planet()
t5=planet()
t6=planet()
t7=planet()
t8=planet()
t9=planet()
def gotovo(event=''):
global t1,t2,t3,t4,t5,t6,t7,t8,t9
t1.solnce()
t2.mercury()
t3.venera()
t4.earth()
t5.mars()
t6.jupiter()
t7.saturn()
t8.uran()
t9.neptun()
while t1.live:
t2.move()
t3.move()
t4.move()
t5.move()
t6.move()
t7.move()
t8.move()
t9.move()
cosmos.update()
time.sleep(0.1)
gotovo()
#
|
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: float
"""
count,ct = 0,0
len1,len2 = len(nums1),len(nums2)
i,j = len1-1,len2-1
lst = []
midnum = (len1+len2+1)/2
ans = 0.0
while count<midnum+1:
n1,n2 =0,0
print("sdfa",count)
if i != -1:
n1 = nums1[i]
if j != -1:
n2 = nums2[j]
if (n1 >= n2)&(i!=-1):
lst.append(n1)
i-=1
elif (j!=-1) &(n1<n2):
lst.append(n2)
j-=1
else:
break
count += 1
if (count-midnum>-1)&(count-midnum<1):
ans += lst[count-1]
ct+=1
print(lst)
if ct == 0:
return 0
return ans/ct
if __name__ == "__main__":
num1 = [1,2,3]
num2 = [4,5,6]
solu =Solution
print(solu.findMedianSortedArrays(solu,num1,num2))
|
a=int(input("Give me one number: "))
b=int(input("Give me another number: "))
print("If you sum those numbers, the values is: ",a+b);
print("If you rest those numbers, the values is: ",a-b);
print("If you multiply those numbers, the values is: ",a*b);
print("If you raise the first number to a power of the second number, the values is: ",a**b);
if b == 0:
print("The quotient for a number divided by 0 is undefined")
else:
print("If you devide the first number with the second number, the value is: ", a/b)
|
input = []
with open('data/02.txt') as f:
for line in f:
line = line.replace(':', '').strip().split(' ')
line[0] = line[0].split('-')
line[0] = [int(x) for x in line[0]]
input.append(line)
valid = 0
for p in input:
a = p[0][0]-1
b = p[0][1]-1
x = p[2][a]
y = p[2][b]
if (p[2][a] == p[1] and p[2][b] != p[1]) or (p[2][a] != p[1] and p[2][b] == p[1]):
valid += 1
print(valid)
|
import threading
import time
import queue
import socket
import select
from pifighterinit import *
'''
def UDPSendToServer(SendStr):
try:
# Open socket and send data - Open it each time as there were problems when comms wasn't great.
with socket.socket(socket.AF_INET, socket.SOCK_DGRAM) as ServerSocket:
# Connect to server and send data
ServerSocket.setblocking(False)
ServerSocket.sendto(bytes(SendStr, "utf-8"), (SERVER_HOST, UDP_PORT))
except:
print ("Send Failure - who cares? Not me.")
'''
# Thread to handle UDP Comms.
class UDPCommsThread (threading.Thread):
def __init__(self, threadID, name, counter):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.counter = counter
def run(self):
global SERVER_HOST
global TCP_PORT
#print ("Starting " + self.name)
with socket.socket(socket.AF_INET, socket.SOCK_DGRAM) as UDPSocket:
UDPSocket.setblocking(False)
while (1):
try:
# Take anything that is in the Queue and send it on to the server.
if (UDPCommSendQueue.empty() == False):
UDPStr = UDPCommSendQueue.get_nowait()
UDPSocket.sendto(bytes(UDPStr, "utf-8"), (SERVER_HOST, UDP_PORT))
# Connect to server and send data
InputSock,OutputSock, ExceptionSock = select.select([UDPSocket], [], [UDPSocket], 0.25)
# Check for any responses
for CommSocket in InputSock:
if CommSocket is UDPSocket:
UDPRecStr = UDPSocket.recv(1024)
#print (UDPRecStr)
UDPCommRecQueue.put_nowait(UDPRecStr)
except:
print ("UDP Send Failure")
raise
'''
if (UDPCommQueue.empty() == False):
UDPStr = UDPCommQueue.get_nowait()
try:
UDPSendToServer (UDPStr)
UDPSocket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
InputSock,OutputSock, ExceptionSock = select.select([UDPSocket], [], [UDPSocket], 0.25)
for CommSocket in InputSock:
if CommSocket is UDPSocket:
UDPRecStr = UDPSocket.recv(1024)
except:
print ("Send Failure - who cares? Not me.")
'''
print ("Exiting " + self.name)
exit()
'''
# Thread to handle the Server communications
class UDPCommsThread (threading.Thread):
def __init__(self, threadID, name, counter):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.counter = counter
def run(self):
print ("Starting " + self.name)
#print_time(self.name, self.counter, 5)
print ("Exiting " + self.name)
'''
# Thread to handle TCP Comms.
class TCPCommsThread (threading.Thread):
def __init__(self, threadID, name, counter):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.counter = counter
def run(self):
global SERVER_HOST
global TCP_PORT
#print ("Starting " + self.name)
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as TCPsocket:
# Connect to server and send data
TCPsocket.connect((SERVER_HOST, TCP_PORT))
print ("TCP Comms")
while (1):
if (TCPCommSendQueue.empty() == False):
TCPStr = TCPCommSendQueue.get_nowait()
try:
TCPsocket.sendall(bytes( TCPStr + "\n", "utf-8"))
# Wait a short period of time for anything on TCP Socket.
InputSock,OutputSock, ExceptionSock = select.select([TCPsocket], [], [TCPsocket], 0.25)
# Go through sockets that got input
for CommSocket in InputSock:
if CommSocket is TCPsocket:
TCPRecStr = TCPsocket.recv(1024)
#print (TCPRecStr)
TCPCommRecQueue.put_nowait(TCPRecStr)
except:
print ("TCP Send Failure")
raise
'''
# Thread to handle the Server communications
class UDPCommsThread (threading.Thread):
def __init__(self, threadID, name, counter):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.counter = counter
def run(self):
print ("Starting " + self.name)
#print_time(self.name, self.counter, 5)
print ("Exiting " + self.name)
'''
# Start the 2 threads to deal with the Comms - UDP for attacks, skips, etc. TCP is used for managing session, etc.
# Both threads are set up a Daemon threads, so they will be killed when the main thread exits.
UDPCommsThread = UDPCommsThread(1, "UDP Data Transmission Thread - real time data might drop some packets.", 1)
UDPCommsThread.setDaemon(True)
UDPCommsThread.start()
TCPCommsThread = TCPCommsThread(1, "TCP Data Transmission Thread - non real time data - manage session, etc.", 1)
TCPCommsThread.setDaemon(True)
TCPCommsThread.start()
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
from app.core.flags import CATEGORY_CHOICES
class Fleet(models.Model):
class Meta:
app_label = u'fleet'
verbose_name = 'Frota'
verbose_name_plural = 'Frotas'
vehicle_name = models.CharField(verbose_name=u'Nome', max_length=255)
category = models.CharField(verbose_name=u'Categoria', max_length=10,
choices=CATEGORY_CHOICES)
description = models.TextField(verbose_name=u'Descrição', max_length=1000,
null=True, blank=True)
is_rented = models.BooleanField(verbose_name=u'Está alugado?',
default=False)
def _validate_cnh_type(self, customer):
can_rent = False
if self.category == 'motorcycle' and 'A' in customer.cnh_type:
can_rent = True
elif self.category == 'car' and 'B' in customer.cnh_type:
can_rent = True
elif self.category == 'utility' and 'C' in customer.cnh_type:
can_rent = True
elif (self.category == 'truck' and
('D' in customer.cnh_type or 'E' in customer.cnh_type)):
can_rent = True
return can_rent
def can_rent(self, customer):
if not self.is_rented:
return self._validate_cnh_type(customer)
def __unicode__(self):
return self.vehicle_name
|
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import time
#driver = webdriver.Firefox(executable_path="D:\SeleniumProject\Web_drivers\geckodriver.exe")
driver = webdriver.Chrome(executable_path="C:\Drivers\chromedriver")
#driver = webdriver.Ie(executable_path="D:\SeleniumProject\Web_drivers\IEDriverServer")
driver.maximize_window()
driver.get("https://react-bootstrap.github.io/components/alerts/")
print(driver.title)
print(driver.current_url)
driver.find_element_by_xpath("/html/body/div[1]/header/div[2]/div[1]/div[3]/div[3]/a").click()
time.sleep(5)
driver.close()
|
# Configuration File for Embedded
libpath = '../lib'
cCompBoxFill = 'grey80' # larger number means lighter grey
cCompBoxOutline = 'grey60'
cConnectFill = 'grey90'
cConnectOutline = 'grey70'
xdefault = '0'
ydefault = '0'
zdefault = '0'
gdefault = '2'
ratio = 1
width = 1280*ratio # deafult 1200
height = 800*ratio # deafult 1000
xmargin = 12*ratio # default 30
ymargin = 5*ratio # default 20
c_width = 200*ratio # width of each small frame , default 400
c_height = 120*ratio # default 100
#theight = 160*ratio # default 280
radius = 15*ratio
distance = c_height/5*ratio
lib1_width = 18
lib2_width = 12
lib_lines = 22
host_lines = 19
mcu_lines = 20
txt_width = 55
font1 = ("white", 8, "bold") # DEFAULT 8
font2 = ("white", 8) # DEFAULT 8
font3 = ("white", 7) # DEFAULT 7
font4 = ("white",6, "bold") # DEFAULT 6
con_scrollx = 200*ratio
con_scrolly = 200*ratio
lib_scrollx = 80*ratio
lib_scrolly = 100*ratio
canvas_bg = '#000000'
selected_color = 'yellow'
read_color = 'CYAN3'
colorlib = [
'AQUAMARINE3',
'AQUAMARINE4',
'BISQUE4',
'BLUE',
'BLUE4',
'BLUEVIOLET',
'BROWN',
'BROWN1',
'BURLYWOOD4',
'CADETBLUE',
'CHARTREUSE4',
'CHOCOLATE3',
'CORNFLOWERBLUE',
'CYAN3',
'CYAN4',
'DARKGOLDENROD',
'DARKGOLDENROD1',
'DARKGREEN',
'DARKORANGE',
'GREENYELLOW',
'HOTPINK',
'LIGHTPINK3',
'LIGHTSLATEGREY',
'DARKORCHID1',
'DARKORCHID4',
'DARKSALMON',
'DARKSEAGREEN4',
'DEEPPINK',
'DEEPSKYBLUE',
'FIREBRICK1',
'GOLD3'
]
|
from . import proprioceptive_humanoid_env
import numpy as np
# All obs but xy but yaw and z use integrals
class LowlevelProprioceptiveHumanoidEnv(proprioceptive_humanoid_env.BaseProprioceptiveHumanoidEnv):
# Initialize environment
def __init__(self):
super(LowlevelProprioceptiveHumanoidEnv, self).__init__()
def _get_obs(self):
s_internal, _ = self.get_intern_extern_state()
return s_internal
|
# В этом упражнении необходимо выполнить задание из нескольких шагов для практики использования регулярных
# выражений и реализации нескольких полезных функций. Следуйте алгоритму:
# 1. Получите текст из файла.
# 2. Разбейте полученный текст на предложения.
# Примечание: Напоминаем, что в русском языке предложения заканчиваются на ., ! или ?.
# 3. Найдите слова, состоящие из 4 букв и более. Выведите на экран 10 самых часто используемых слов.
# Пример вывода: [(“привет”, 3), (“люди”, 3), (“город”, 2)].
# 4. Отберите все ссылки.
# Примечание: Для поиска воспользуйтесь методом compile, в который вы вставите свой шаблон для поиска ссылок в тексте.
# 5. Ссылки на страницы какого домена встречаются чаще всего?
# Напоминаем, что доменное имя — часть ссылки до первого символа «слеш». Например в ссылке вида
# travel.mail.ru/travel?id=5 доменным именем является travel.mail.ru.
# Подсчет частоты сделайте по аналогии с заданием 3, но верните только одну самую частую ссылку.
# 6. Замените все ссылки на текст «Ссылка отобразится после регистрации».
import re
from collections import Counter
with open('text.txt', 'r', encoding='utf-8') as f:
text = f.read()
# 2) Разбиваем на предложения
task2 = re.split(r'[\.!?]\s', text)
print('2) Текст разбитый на предложения:', end='\n ')
print(*task2, sep='\n ')
print('-' * 100)
# 3. Найдите слова, состоящие из 4 букв и более. Выведите на экран 10 самых часто используемых слов.
task3 = re.findall(r'\w{4}\w*', text)
count = Counter(task3).most_common(10)
print(f'3) Десятка самых популярных слов с количеством букв >= 4:\n {count}')
print('-' * 100)
# 4. Отберите все ссылки. Используем compile
re4 = re.compile(r'(((http|https):\/\/)?(www[0-9]\.)?([\w-]+\.{1})+([A-Za-z]{2,4})(\/\??\w+)*)')
task4 = [i[0] for i in re4.findall(text)]
print(f'4) Все ссылки из текста:', end='\n ')
print(*task4, sep=', ')
print('-' * 100)
# 5. Самые частые домены в ссылках
re5 = re.compile(r'((http|https):\/\/)?(www[0-9]\.)?(([\w-]+\.{1})+([A-Za-z]{2,4}))\/?')
task5 = [i[3] for i in re5.findall(text)]
count = Counter(task5).most_common(1)
print(f'5) Самый частый домен в ссылках:\n {count[0][0]}')
print('-' * 100)
# 6. Замените все ссылки на текст «Ссылка отобразится после регистрации».
task6 = re4.sub('«Ссылка отобразится после регистрации»', text)
print(f'6) Текст с измененными ссылками:\n {task6}')
|
STATUS = {
"Suspend": "Suspended",
"Completed": "Completed",
"Canceled": "Canceled",
"Sent": "Requested",
"Discontinued": "Aborted",
"Denied Approval": "Rejected",
"Verified": "Verified",
"Pending": "Received",
"Resulted": "Completed",
"Dispensed": "Active",
"Pending Verify": "Accepted",
"Holding for Referral": "Other"
}
TYPE_MAP = {
"ABD RETROPERIT, RENAL & BLADDER US - GHR": "IMAGING",
"ABLAT,OPEN,1+ LIVER TUMOR(S),PERCUT RF": "IMAGING",
"ABLATION >1 BONE TUMOR(S) SOFT TISSUE BY TUMOR EXTENSION PERCUT": "IMAGING",
"ABSCESS DRAINAGE X-RAY/US/CT CTRL": "IMAGING",
"ABSCESS IMAGING, WHOLE BODY": "IMAGING",
"ACUTE GI BLOOD LOSS IMAGING": "IMAGING",
"ACUTE VENOUS THROMBOSIS IMAGING, PEPTIDE": "IMAGING",
"ADRENAL NUCLEAR IMAGING": "IMAGING",
"AEEG MONITORING 24 HOURS": "IMAGING",
"AEROSOL LUNG IMAGE, SINGLE": "IMAGING",
"ANES ABLATION BONE TUMOR RADIOFREQ PERQ": "IMAGING",
"ANES AV FISTULA REVISION,OPEN": "IMAGING",
"ANES BALLOON DILATION INTRACRANIAL VASOSPASM, INIT": "IMAGING",
"ANES BONE IMAGING (SPECT)": "IMAGING",
"ANES BONE IMAGING WHOLE BODY": "IMAGING",
"ANES BRAIN FLOW IMAGING ONLY": "IMAGING",
"ANES BRAIN IMAGING SPECT": "IMAGING",
"ANES BRAIN LTD IMAGING & FLOW": "IMAGING",
"ANES CARDIAC MRI W MORPH AND FUNCTION WO CONTRAST": "IMAGING",
"ANES CARDIAC MRI W MORPH AND FUNTION WO CONTRAST FOL BY CONTRAST": "IMAGING",
"ANES CAT ABD; W/CONTRAST": "IMAGING",
"ANES CAT ABD; WO CONTRAST THEN W/CONTRAS": "IMAGING",
"ANES CAT HEAD/BRAIN; WO CONTRAST FOLLOWE": "IMAGING",
"ANES CAT HEAD/BRAIN; WO CONTRAST MAT": "IMAGING",
"ANES CAT MAXILLOFACIAL; WO CONTRAST": "IMAGING",
"ANES CAT MAXILLOFACIAL; WO CONTRAST THEN": "IMAGING",
"ANES CAT ORBIT/SELLA/OUTER-MID-INNER EAR": "IMAGING",
"ANES CAT PELVIS; W/CONTRAST": "IMAGING",
"ANES CAT SOFT TISS NECK; W/CONTRAST": "IMAGING",
"ANES CAT THORAX; W/CONTRAST MAT": "IMAGING",
"ANES CHANGE URETER STENT, PERCUT": "IMAGING",
"ANES CHANGE URETERAL STENT VIA TRANSURETH": "IMAGING",
"ANES COMPUTED TOMOGRAPHIC ANGIOGRAPHY ABD AND PELVIS W CONTRA": "IMAGING",
"ANES CT ABDOMEN AND PELVIS W AND W/O CONTRAST": "IMAGING",
"ANES CT ABDOMEN AND PELVIS W/OUT CONTRAST": "IMAGING",
"ANES CT ABDOMEN AND PELVIS WITH CONTRAST": "IMAGING",
"ANES CT ANGIOGRAM ABD AORTA BILAT ILIOFEMORAL": "IMAGING",
"ANES CT ANGIOGRAM ABDOMEN": "IMAGING",
"ANES CT ANGIOGRAM CHEST": "IMAGING",
"ANES CT ANGIOGRAM HEAD": "IMAGING",
"ANES CT ANGIOGRAM HEART": "IMAGING",
"ANES CT ANGIOGRAM LOWER EXTREMITY": "IMAGING",
"ANES CT ANGIOGRAM NECK": "IMAGING",
"ANES CT ANGIOGRAM PELVIS": "IMAGING",
"ANES CT ANGIOGRAM UPPER EXTREMITY": "IMAGING",
"ANES CT CERV SPINE NO CONTRAST": "IMAGING",
"ANES CT CERV SPINE W/CONTRAST": "IMAGING",
"ANES CT CHEST COMBO": "IMAGING",
"ANES CT CHEST NO CONTRAST": "IMAGING",
"ANES CT COLONOSCOPY DIAGNOSTIC W OUT CONTRAST": "IMAGING",
"ANES CT COLONOSCOPY SCREENING": "IMAGING",
"ANES CT HEAD/BRAIN CONTRAST": "IMAGING",
"ANES CT HEART W CONTRAST FOR EVAL CONG HEART DISEASE": "IMAGING",
"ANES CT HEART W CONTRAST FOR EVAL OF CARIAC STRUCTURE": "IMAGING",
"ANES CT HEART WO CONTRAST W QUANT EVAL CALCIUM": "IMAGING",
"ANES CT LOWER EXTREMITY W CONTRAST": "IMAGING",
"ANES CT LOWER EXTREMITY W WO CONTRAST": "IMAGING",
"ANES CT LOWER EXTREMITY WO CONTRAST": "IMAGING",
"ANES CT LUMBAR SPINE NO CONTRAST": "IMAGING",
"ANES CT LUMBAR SPINE W/CONTRAST": "IMAGING",
"ANES CT NECK TISSUE COMBO": "IMAGING",
"ANES CT SCAN FACE/SINUS CONTRAST": "IMAGING",
"ANES CT SCAN OF ABDOMEN": "IMAGING",
"ANES CT SCAN OF NECK TISSUE": "IMAGING",
"ANES CT SCAN OF PELVIS": "IMAGING",
"ANES CT SCAN OF PELVIS COMBO": "IMAGING",
"ANES CT SCAN SKULL COMBO": "IMAGING",
"ANES CT SCAN SKULL CONTRAST": "IMAGING",
"ANES CT THORACIC SPINE NO CONTRAST": "IMAGING",
"ANES CT THORACIC SPINE W/CONTRAST": "IMAGING",
"ANES CT UPPER EXTREMITY W CONTRAST": "IMAGING",
"ANES CT UPPER EXTREMITY WO CONTRAST": "IMAGING",
"ANES DUPLEX SCAN-EXTREM VEINS; UNILAT/LT": "IMAGING",
"ANES ECG TRANSESOPH": "IMAGING",
"ANES ECHO BREAST(S) B-SCAN &/OR REAL TIM": "IMAGING",
"ANES ECHO RETROPERITON B-SCAN W/IMAGE DO": "IMAGING",
"ANES ECHO TRANSESOPH REAL-TIME; W/PROBE": "IMAGING",
"ANES ECHO TRANSESOPH; IMAGE ACQUISIT": "IMAGING",
"ANES ECHO TRANSRECTAL": "IMAGING",
"ANES EMBOLIZATION UTERINE FIBROID": "IMAGING",
"ANES ENDOVENOUS LASER, 1ST VEIN": "IMAGING",
"ANES ENDOVSC TMP BALLN ART OCCL HEAD/NCK": "IMAGING",
"ANES FLUORO (SEP PRO) TO 1 HR TIME": "IMAGING",
"ANES FLUORO PHYS TIME 1 HR-ASSIST NON-": "IMAGING",
"ANES INSERT GASTROSTOMY TUBE PERC": "IMAGING",
"ANES INSERTION PERIPHLY INSRT CVAD SUBQ": "IMAGING",
"ANES INSERTION PERIPHLY INSRT CVAD W/SUB": "IMAGING",
"ANES INSERTION PICC W/O SUBQ PORT/PUMP;": "IMAGING",
"ANES INSRT TRNS INTRAHEP PORTOSYS SHNT": "IMAGING",
"ANES INSRT TUNNL CNTRL CVAD 2 CATH VIA 2": "IMAGING",
"ANES INSRT TUNNL CNTRL CVAD 2 CATH-2 SIT": "IMAGING",
"ANES INSRT TUNNLD CNTRLLY CV ACSS DEVC W": "IMAGING",
"ANES INSRT TUNNLD CNTRLLY CVC NO SUBQPOR": "IMAGING",
"ANES INSRT TUNNLD CNTRLLY INSRT CVAD SUB": "IMAGING",
"ANES INSRTION NON-TUNNLD CNTRLLY INSRT C": "IMAGING",
"ANES INTRACRANIAL BALLOON ANGIOPLASTY": "IMAGING",
"ANES MECH REMV PERICATH OBST MATL CV DEV": "IMAGING",
"ANES MR ANGIOGRAPHY HEAD W/O DYE": "IMAGING",
"ANES MR ANGIOGRAPHY HEAD W/O&W DYE": "IMAGING",
"ANES MR ANGIOGRAPHY NECK W/DYE": "IMAGING",
"ANES MRA HEAD W/CONTRAST": "IMAGING",
"ANES MRA NECK COMBO": "IMAGING",
"ANES MRA NECK NO CONTRAST": "IMAGING",
"ANES MRI ABDOMEN CONTRAST": "IMAGING",
"ANES MRI ABDOMEN W/O&W DYE": "IMAGING",
"ANES MRI ANGIO ABD W/WO CONTRAST MAT": "IMAGING",
"ANES MRI ANGIO UPPER EXTREM W/WO CONTRAS": "IMAGING",
"ANES MRI ANGIOGRAM CHEST": "IMAGING",
"ANES MRI ANGIOGRAM LOWER EXTREMITY": "IMAGING",
"ANES MRI ANGIOGRAM PELVIS": "IMAGING",
"ANES MRI ANY JT LOWER EXTREM": "IMAGING",
"ANES MRI ANY JT UPPER EXTREM": "IMAGING",
"ANES MRI BRAIN W/CONTRAST": "IMAGING",
"ANES MRI BRAIN WO CONTRAST": "IMAGING",
"ANES MRI BRAIN WO CONTRAST FOLLOWED BY C": "IMAGING",
"ANES MRI BREAST W/WO CONTR UNILATERAL": "IMAGING",
"ANES MRI BREAST WO &/OR W/CONTRAST; BIL": "IMAGING",
"ANES MRI CHEST COMBO": "IMAGING",
"ANES MRI CHEST NO CONTRAST": "IMAGING",
"ANES MRI CHEST W/CONTRAST": "IMAGING",
"ANES MRI FACE/NECK COMBO": "IMAGING",
"ANES MRI LOWER EXTREM JOINT W CONTRAST": "IMAGING",
"ANES MRI LOWER EXTREM JOINT W WO CONTRAST": "IMAGING",
"ANES MRI LOWER EXTREMITY W CONTRAST": "IMAGING",
"ANES MRI LOWER EXTREMITY W WO CONTRAST": "IMAGING",
"ANES MRI LOWER EXTREMITY WO CONTRAST": "IMAGING",
"ANES MRI LUMBAR SPINE W/CONTRAST": "IMAGING",
"ANES MRI PELVIS W CONTRAST": "IMAGING",
"ANES MRI PELVIS W/O&W DYE": "IMAGING",
"ANES MRI SPECTROSCOPY": "IMAGING",
"ANES MRI SPINAL CANAL & CONTENTS CERV; W": "IMAGING",
"ANES MRI SPINAL CANAL & CONTENTS LUMBAR;": "IMAGING",
"ANES MRI SPINAL CANAL & CONTENTS THORACI": "IMAGING",
"ANES MRI SPINAL CANAL WO THEN W/CONT; CE": "IMAGING",
"ANES MRI SPINAL CANAL WO THEN W/CONT; LU": "IMAGING",
"ANES MRI SPINAL CANAL WO THEN W/CONT; TH": "IMAGING",
"ANES MRI TEMPORAL MANDIBULAR JT": "IMAGING",
"ANES MRI THORACIC SPINE W/CONTRAST": "IMAGING",
"ANES MRI UPPER EXTREM OTHER THAN JT": "IMAGING",
"ANES MRI UPPER EXTREMITY JOINT W CONTRAST": "IMAGING",
"ANES MRI UPPER EXTREMITY JOINT W WO CONTRAST": "IMAGING",
"ANES MRI UPPER EXTREMITY W CONTRAST": "IMAGING",
"ANES MRI UPPER EXTREMITY WO CONTRAST": "IMAGING",
"ANES MRI, FACE, NECK": "IMAGING",
"ANES MRI-ORBIT/FACE/NECK W/CONTRAST": "IMAGING",
"ANES NM RENAL FLOW FUNC W/PHARM": "IMAGING",
"ANES PERCUT ABLATE LIVER RF": "IMAGING",
"ANES PERCUT MECH THROMBECTOMY, VENOUS": "IMAGING",
"ANES PET BRAIN IMAGING METABOLIC EVALUATION": "IMAGING",
"ANES PET CT LIMITED AREA": "IMAGING",
"ANES PET CT WHOLE BODY": "IMAGING",
"ANES PET TUMOR IMAGING W/CT; SKULL BASE": "IMAGING",
"ANES PSEUDOANEURYSM INJECTION TRT": "IMAGING",
"ANES RADN RX DELIVERY SIMPLE =<5 MEV": "IMAGING",
"ANES REMOVE URETERAL STENT VIA TRANSURETH": "IMAGING",
"ANES RENAL FLOW/FUNCT IMAGE COMBO PHARM": "IMAGING",
"ANES REPL CATH ONLY CVAD SUBQ PORT/PUMP": "IMAGING",
"ANES REPL CMPL PERIPHLY INSRT CVAD W/SUB": "IMAGING",
"ANES REPL CMPL PICC NO SUBQ PORT/PUMP TH": "IMAGING",
"ANES REPL CMPL TUNNLD CNTRLLY CVC W/O SU": "IMAGING",
"ANES REPL CMPL TUNNLD CNTRLLY INSRT CVAD": "IMAGING",
"ANES REPLACE GASTROSTOMY/CECOSTOMY TUBE PERCUTANEOUS": "IMAGING",
"ANES REPLACEMENT GASTRO-JEJUNOSTOMY TUBE PERCUTANEOUS": "IMAGING",
"ANES REPSTN PREVIOUSLY PLCD CVC UNDER FL": "IMAGING",
"ANES REV TRNS INTRAHEP PORTOSYS SHNT": "IMAGING",
"ANES TUMOR IMAGING-PET-METABOLIC EVAL": "IMAGING",
"ANES ULTRASOUND,RENAL AORTA": "IMAGING",
"ANES URETHROCYSTOGRAPHY VOIDING-RAD S &": "IMAGING",
"ANES UROGRAPHY ANTEGRADE": "IMAGING",
"ANES UROGRAPHY IV W/WO KUB W/WO TOMOGRAP": "IMAGING",
"ANES UROGRAPHY RETROGRADE W/WO KUB": "IMAGING",
"ANES X-RAY ABDOMEN 2 VW": "IMAGING",
"ANES X-RAY ELBOW 2 VW": "IMAGING",
"ANES X-RAY LEG, INFANT 2 VW": "IMAGING",
"ANES X-RAY NECK SOFT TISSUE": "IMAGING",
"ANES X-RAY NOSE-RECTUM CHILD F.B.": "IMAGING",
"ANES X-RAY PELVIS/HIPS CHILD/INFANT": "IMAGING",
"ANES XRAY BONE SURVEY INFANT": "IMAGING",
"ARTHROGRAM HIP RIGHT": "IMAGING",
"ARTHROGRAM OF ANKLE": "IMAGING",
"ARTHROGRAM OF ELBOW": "IMAGING",
"ARTHROGRAM OF KNEE": "IMAGING",
"ARTHROGRAM OF SHOULDER": "IMAGING",
"ARTHROGRAM OF WRIST": "IMAGING",
"ASSESSMENT-EXTERNAL": "IMAGING",
"ATHERECTOMY TRANSLUMNL RENAL": "IMAGING",
"ATHERECTOMY TRANSLUMNL VISC ADDNL": "IMAGING",
"ATHERECTOMY TRANSLUMNL VISCERAL": "IMAGING",
"AUDITORY EVOKED RESPONSE": "IMAGING",
"AUTOPSY": "PATHOLOGY",
"BALLOON ANGIO VENOUS": "IMAGING",
"BALLOON DILAT INTRACRAN VASOSPASM, ADD DIFF FAM": "IMAGING",
"BALLOON DILAT INTRACRAN VASOSPASM, ADD SAME FAM": "IMAGING",
"BALLOON DILATION INTRACRANIAL VASOSPASM, INIT": "IMAGING",
"BD DEXA APPENDICULAR SKELETON": "IMAGING",
"BD DEXA AXIAL SKELETON": "IMAGING",
"BD DEXA AXIAL SKELETON AND APPENDICULAR": "IMAGING",
"BD DEXA AXIAL SKELETON W/VERTEBRAL FX ASSESS": "IMAGING",
"BD DEXA TOTAL BODY COMPOSITION": "IMAGING",
"BD DEXA VERTEBRAL FX ASSESS ONLY": "IMAGING",
"BD UNLISTED": "IMAGING",
"BLOOD VOLUME": "IMAGING",
"BLOOD/LYMPH NUCLEAR EXAM UNLISTED": "IMAGING",
"BONE DENSITY DXA APPENDICULAR SKELETON ONE OR MORE": "IMAGING",
"BONE IMAGING (SPECT)": "IMAGING",
"BONE IMAGING LIMITED AREA": "IMAGING",
"BONE IMAGING WHOLE BODY": "IMAGING",
"BONE IMAGING, 3 PHASE": "IMAGING",
"BONE IMAGING, MULTIPLE AREAS": "IMAGING",
"BONE MARROW IMAGING, BODY": "IMAGING",
"BONE MARROW IMAGING, LTD": "IMAGING",
"BONE MARROW IMAGING, MULT": "IMAGING",
"BONE MARROW PATHOLOGY": "PATHOLOGY",
"BONE MINERAL, DUAL PHOTON": "IMAGING",
"BONE MINERAL, SINGLE PHOTON": "IMAGING",
"BONE WINDOWS": "IMAGING",
"BRACHYTHER DOSE PLAN INTERM": "IMAGING",
"BRACHYTHER DOSE PLAN SIMPLE": "IMAGING",
"BRAF MUTATION": "PATHOLOGY",
"BRAIN FLOW IMAGING ONLY": "IMAGING",
"BRAIN IMAGING COMP & FLOW": "IMAGING",
"BRAIN IMAGING PET PERFUSION": "IMAGING",
"BRAIN IMAGING SPECT": "IMAGING",
"BRAIN IMAGING, COMPLETE": "IMAGING",
"BRAIN IMAGING, LTD STATIC": "IMAGING",
"BRAIN LTD IMAGING & FLOW": "IMAGING",
"BRAINSTEM AUDITORY EVOKED POTENTIAL": "IMAGING",
"BRONCHOGRAM, BILAT": "IMAGING",
"CAD BREAST MRI": "IMAGING",
"CAD DIAGNOSITC MAMMOGRAPHY": "IMAGING",
"CAD DIAGNOSTIC MAMMOGRAPHY": "IMAGING",
"CAD SCREENING MAMMOGRAPHY": "IMAGING",
"CAD, DIAGNOSTIC MAMOGRAPHY": "IMAGING",
"CAN'T FIND CT": "IMAGING",
"CAN'T FIND FLUOROSCOPY": "IMAGING",
"CAN'T FIND MAMMOGRAPHY": "IMAGING",
"CAN'T FIND MRI": "IMAGING",
"CAN'T FIND NUCLEAR MEDICINE": "IMAGING",
"CAN'T FIND PET": "IMAGING",
"CAN'T FIND ULTRASOUND": "IMAGING",
"CAN'T FIND X-RAY": "IMAGING",
"CARDIAC CALCIUM SCORING": "IMAGING",
"CARDIAC MAGNETIC RESONANCE IMAG VELOCITY FLOW MAPPING ": "IMAGING",
"CARDIAC MRI W MORPH AND FUNCTION WO CONTRAST": "IMAGING",
"CARDIAC MRI W MORPH AND FUNCTION WO CONTRAST FOL BY CONTRAST W STRESS": "IMAGING",
"CARDIAC MRI W MORPH AND FUNTION WO CONTRAST FOL BY CONTRAST": "IMAGING",
"CARDIAC MRI W MORPH AND FUNTION WO CONTRAST W STRESS": "IMAGING",
"CARDIAC SCORING": "IMAGING",
"CARDIAC SHUNT IMAGING": "IMAGING",
"CARDIOVASC NUCL EXAM UNLISTED": "IMAGING",
"CAROTID IMT": "IMAGING",
"CENTRAL MOTOR EVOKED POTENTIAL STUDY - UPPER AND LOWER LIMB": "IMAGING",
"CEREBRAL BLOOD FLOW IMAGING": "IMAGING",
"CEREBRAL PERFUSION ANALYSIS USING CT W CONTRAST": "IMAGING",
"CHANGE EXTERNAL NEPHROURETERAL CATHETER WITH FLUOROSCOPIC GUIDENCE": "IMAGING",
"CHANGE PERCUT TUBE/DRAIN CATH": "IMAGING",
"CHANGE URETER STENT, PERCUT": "IMAGING",
"CHANGE URETERAL STENT VIA TRANSURETH": "IMAGING",
"CHEST X-RAY STEREO PA": "IMAGING",
"CHROMOSOME ANALYSIS POC WITH MICROARRAY REFLEX": "PATHOLOGY",
"CINE ESOPHAGRAM PHARYNX": "IMAGING",
"CINEMATIC AS ADDN TO X-RAY": "IMAGING",
"CINEMATIC X-RAYS": "IMAGING",
"CISTERNOGRAPHY,POS CONTRAST": "IMAGING",
"COLLAGEN PROFILE INTERPRETATION": "PATHOLOGY",
"COLOREC CANC SCRN,BARIUM ENEMA": "IMAGING",
"COMMONN CAROTID INTIMA MEDIA THICKNESS STUDY FOR EVAL ": "IMAGING",
"COMPLEX TOMOGRAM BILAT": "IMAGING",
"COMPLEX TOMOGRAM UNILAT": "IMAGING",
"COMPUTED TOMOGRAPHIC ANGIOGRAPHY ABD AND PELVIS W CONTRA": "IMAGING",
"COMPUTER AID DECT DX/SCRN MAMO": "IMAGING",
"CONTRAST INJ CENT VEN CATH, INC FLOURO": "IMAGING",
"CONTRAST INJECTION PERCUTANEOUOS RADIOLOGIC EVAL GI TUBE": "IMAGING",
"CONTRAST X-RAY OF LARYNX": "IMAGING",
"CONVERT GASTROSTOMY-GASTRO-JEJUNOSTOMY TUBE PERCUTANEOUS": "IMAGING",
"COSMETIC PHOTODYNAMIC THERAPY 1ST TX": "IMAGING",
"COSMETIC PHOTODYNAMIC THERAPY 2ND TX": "IMAGING",
"COSMETIC PHOTODYNAMIC THERAPY ACNE TX": "IMAGING",
"CSF FLUID SCAN CISTERNOGRAPHY": "IMAGING",
"CSF LEAKAGE IMAGING": "IMAGING",
"CSF SCAN SPECT": "IMAGING",
"CSF SHUNT EVALUATION": "IMAGING",
"CSF VENTRICULOGRAPHY": "IMAGING",
"CT 3D RENDERING": "IMAGING",
"CT ABD/PEL W/CON ATTN-PANCREAS": "IMAGING",
"CT ABD/PEL W/CONT ATTN-ADRENAL": "IMAGING",
"CT ABD/PEL W/CONT ATTN-KIDNEY": "IMAGING",
"CT ABD/PEL W/CONT ATTN-LIVER": "IMAGING",
"CT ABD/PEL W/CONT KIDNEY STONE": "IMAGING",
"CT ABD/PEL W/O CONTRAST": "IMAGING",
"CT ABD/PEL WITH CONTRAST": "IMAGING",
"CT ABDO/PELVIS NO CONTRAST": "IMAGING",
"CT ABDO/PELVIS W/CONTRAST": "IMAGING",
"CT ABDOMEN": "IMAGING",
"CT ABDOMEN AND PELVIS W AND W/O CONTRAST": "IMAGING",
"CT ABDOMEN AND PELVIS W/OUT CONTRAST": "IMAGING",
"CT ABDOMEN AND PELVIS WITH CONTRAST": "IMAGING",
"CT ABDOMEN COMBO ": "IMAGING",
"CT ABDOMEN CYBER KNIFE": "IMAGING",
"CT ABDOMEN CYBER KNIFE W CONTRAST": "IMAGING",
"CT ABDOMEN CYBER KNIFE W WO CONTRAST": "IMAGING",
"CT ABDOMEN CYBER KNIFE WO CONTRAST": "IMAGING",
"CT ABDOMEN NO CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS": "IMAGING",
"CT ABDOMEN PELVIS FOR KIDNEY STONES": "IMAGING",
"CT ABDOMEN PELVIS FOR KIDNEY STONES W CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS FOR KIDNEY STONES W WO CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS FOR KIDNEY STONES WO CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS LIMITED W CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS LIMITED W WO CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS LIMITED WO CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS WO CONTRAST": "IMAGING",
"CT ABDOMEN PELVIS WO W CONTRAST": "IMAGING",
"CT ABDOMEN W CONTRAST": "IMAGING",
"CT ABDOMEN W WO PELVIS W CONTRAST": "IMAGING",
"CT ABDOMEN W WO PELVIS WO CONTRAST": "IMAGING",
"CT ABDOMEN W/CONTRAST": "IMAGING",
"CT ABDOMEN WO CONTRAST": "IMAGING",
"CT ABDOMEN WO W CONTRAST": "IMAGING",
"CT ABDOMEN WO W PELVIS W": "IMAGING",
"CT ABDOMEN(ADRENAL)COMBO": "IMAGING",
"CT ABDOMEN(ADRENAL)NO CONTRAST": "IMAGING",
"CT ABDOMEN(ADRENAL)W/CONTRAST": "IMAGING",
"CT ABDOMEN(KIDNEY)COMBO": "IMAGING",
"CT ABDOMEN(KIDNEY)NO CONTRAST": "IMAGING",
"CT ABDOMEN(KIDNEY)W/CONTRAST": "IMAGING",
"CT ABDOMEN(LIVER)COMBO": "IMAGING",
"CT ABDOMEN(LIVER)NO CONTRAST": "IMAGING",
"CT ABDOMEN(LIVER)W/CONTRAST": "IMAGING",
"CT ABDOMEN(PANCREAS)COMBO": "IMAGING",
"CT ABDOMEN(PANCREAS)NO CONT": "IMAGING",
"CT ABDOMEN(PANCREAS)W/CONTRAST": "IMAGING",
"CT ABDOMEN(STONE)COMBO ": "IMAGING",
"CT ABDOMEN(STONE)W/CONTRAST": "IMAGING",
"CT ABDOMEN/PELVIS COMBO": "IMAGING",
"CT ADRENAL GLANDS": "IMAGING",
"CT ADRENAL GLANDS W CONTRAST": "IMAGING",
"CT ADRENAL GLANDS W WO CONTRAST": "IMAGING",
"CT ANGIO ABD AORTA BILAT ILIOFEM W LEG RUNOFF W CONTRAST": "IMAGING",
"CT ANGIO ABD AORTA BILAT ILIOFEM W LEG RUNOFF W WO CONTRAST": "IMAGING",
"CT ANGIO ABD AORTA W ILEO FEM": "IMAGING",
"CT ANGIO ABDOMEN": "IMAGING",
"CT ANGIO CHEST": "IMAGING",
"CT ANGIO CHEST ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT ANGIO CHEST ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT ANGIO HEAD": "IMAGING",
"CT ANGIO LOWER EXTREM W CONTRAST LEFT": "IMAGING",
"CT ANGIO LOWER EXTREM W CONTRAST RIGHT": "IMAGING",
"CT ANGIO LOWER EXTREM W WO CONTRAST LEFT": "IMAGING",
"CT ANGIO LOWER EXTREM W WO CONTRAST RIGHT": "IMAGING",
"CT ANGIO LOWER EXTREMITY": "IMAGING",
"CT ANGIO LOWER EXTREMITY W CONTRAST BILAT": "IMAGING",
"CT ANGIO LOWER EXTREMITY W WO CONTRAST BILATERAL": "IMAGING",
"CT ANGIO NECK": "IMAGING",
"CT ANGIO PELVIS": "IMAGING",
"CT ANGIO UPPER EXTREM W WO CONTRAST LEFT": "IMAGING",
"CT ANGIO UPPER EXTREMITY": "IMAGING",
"CT ANGIO UPPER EXTREMITY W CONTRAST LEFT": "IMAGING",
"CT ANGIO UPPER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"CT ANGIO UPPPER EXTREMITY W WO CONTRAST RIGHT": "IMAGING",
"CT ANGIOGRAM ABD AORTA BILAT ILIOFEMORAL": "IMAGING",
"CT ANGIOGRAM ABD AORTA ILIOFEM BILAT W LEG RUNOFF": "IMAGING",
"CT ANGIOGRAM ABDOMEN": "IMAGING",
"CT ANGIOGRAM ABDOMEN PELVIS": "IMAGING",
"CT ANGIOGRAM ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT ANGIOGRAM ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM ABDOMEN W CONTRAST": "IMAGING",
"CT ANGIOGRAM ABDOMEN W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM CHEST": "IMAGING",
"CT ANGIOGRAM CHEST ABDOMEN": "IMAGING",
"CT ANGIOGRAM CHEST ABDOMEN PELVIS": "IMAGING",
"CT ANGIOGRAM CHEST ABDOMEN W CONTRAST": "IMAGING",
"CT ANGIOGRAM CHEST ABDOMEN W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM CHEST PE IMAGING- 3D": "IMAGING",
"CT ANGIOGRAM CHEST W CONTRAST": "IMAGING",
"CT ANGIOGRAM CHEST W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM CORONARY ARTERIES": "IMAGING",
"CT ANGIOGRAM HEAD": "IMAGING",
"CT ANGIOGRAM HEAD AND NECK": "IMAGING",
"CT ANGIOGRAM HEAD AND NECK LEVEL 1": "IMAGING",
"CT ANGIOGRAM HEAD AND NECK W CONTRAST LEVEL 1": "IMAGING",
"CT ANGIOGRAM HEAD AND NECK W WO CONTRAST LEVEL 1": "IMAGING",
"CT ANGIOGRAM HEAD LEVEL 1": "IMAGING",
"CT ANGIOGRAM HEAD NECK W CONTRAST": "IMAGING",
"CT ANGIOGRAM HEAD NECK W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM HEAD STRYKER": "IMAGING",
"CT ANGIOGRAM HEAD STRYKER W CONTRAST": "IMAGING",
"CT ANGIOGRAM HEAD STRYKER W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM HEAD W CONTRAST": "IMAGING",
"CT ANGIOGRAM HEAD W CONTRAST LEVEL 1": "IMAGING",
"CT ANGIOGRAM HEAD W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM HEAD W WO CONTRAST LEVEL 1": "IMAGING",
"CT ANGIOGRAM HEART": "IMAGING",
"CT ANGIOGRAM LOWER EXTREMITY": "IMAGING",
"CT ANGIOGRAM LOWER EXTREMITY BILATERAL": "IMAGING",
"CT ANGIOGRAM LOWER EXTREMITY LEFT": "IMAGING",
"CT ANGIOGRAM LOWER EXTREMITY RIGHT": "IMAGING",
"CT ANGIOGRAM NECK": "IMAGING",
"CT ANGIOGRAM NECK W CONTRAST": "IMAGING",
"CT ANGIOGRAM NECK W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM PELVIS": "IMAGING",
"CT ANGIOGRAM PELVIS W CONTRAST": "IMAGING",
"CT ANGIOGRAM PELVIS W WO CONTRAST": "IMAGING",
"CT ANGIOGRAM THORACIC AORTA": "IMAGING",
"CT ANGIOGRAM UPPER EXTREMITY": "IMAGING",
"CT ANGIOGRAM UPPER EXTREMITY BILAT WO W CONTRAST": "IMAGING",
"CT ANGIOGRAM UPPER EXTREMITY LEFT": "IMAGING",
"CT ANGIOGRAM UPPER EXTREMITY RIGHT": "IMAGING",
"CT ANKLE LEFT": "IMAGING",
"CT ANKLE RIGHT": "IMAGING",
"CT ANKLE W CONTRAST LEFT": "IMAGING",
"CT ANKLE W CONTRAST RIGHT": "IMAGING",
"CT ANKLE W WO CONTRAST LEFT": "IMAGING",
"CT ANKLE W WO CONTRAST RIGHT": "IMAGING",
"CT ANKLE WO CONTRAST LEFT": "IMAGING",
"CT ANKLE WO CONTRAST RIGHT": "IMAGING",
"CT ARM LEFT": "IMAGING",
"CT ARM RIGHT": "IMAGING",
"CT ARM W CONTRAST LEFT": "IMAGING",
"CT ARM W CONTRAST RIGHT": "IMAGING",
"CT ARM W WO CONTRAST LEFT": "IMAGING",
"CT ARM W WO CONTRAST RIGHT": "IMAGING",
"CT ARM WO CONTRAST LEFT": "IMAGING",
"CT ARM WO CONTRAST RIGHT": "IMAGING",
"CT ARTHROGRAM ANKLE LEFT": "IMAGING",
"CT ARTHROGRAM ANKLE RIGHT": "IMAGING",
"CT ARTHROGRAM ELBOW LEFT": "IMAGING",
"CT ARTHROGRAM ELBOW RIGHT": "IMAGING",
"CT ARTHROGRAM HIP": "IMAGING",
"CT ARTHROGRAM HIP LEFT": "IMAGING",
"CT ARTHROGRAM HIP RIGHT": "IMAGING",
"CT ARTHROGRAM KNEE": "IMAGING",
"CT ARTHROGRAM KNEE LEFT": "IMAGING",
"CT ARTHROGRAM KNEE RIGHT": "IMAGING",
"CT ARTHROGRAM SHOULDER": "IMAGING",
"CT ARTHROGRAM SHOULDER LEFT": "IMAGING",
"CT ARTHROGRAM SHOULDER RIGHT": "IMAGING",
"CT ARTHROGRAM WRIST LEFT": "IMAGING",
"CT ARTHROGRAM WRIST RIGHT": "IMAGING",
"CT BONE DENSITOMETRY STUDY": "IMAGING",
"CT BONE DENSITY, AXIAL": "IMAGING",
"CT BONY PELVIS": "IMAGING",
"CT BONY PELVIS WO CONTRAST": "IMAGING",
"CT CARDIAC CALCIUM SCORING": "IMAGING",
"CT CARDIAC CALCIUM SCORING - CASH SERVICE": "IMAGING",
"CT CEREBRAL PERFUSION": "IMAGING",
"CT CEREBRAL PERFUSION LEVEL 1": "IMAGING",
"CT CEREBRAL PERFUSION W CONTRAST": "IMAGING",
"CT CEREBRAL PERFUSION W CONTRAST LEVEL 1": "IMAGING",
"CT CEREBRAL PERFUSION W WO CONTRAST": "IMAGING",
"CT CEREBRAL PERFUSION W WO CONTRAST LEVEL 1": "IMAGING",
"CT CERV SPINE COMBO": "IMAGING",
"CT CERV SPINE NO CONTRAST": "IMAGING",
"CT CERV SPINE W/CONTRAST": "IMAGING",
"CT CERVICAL SPINE": "IMAGING",
"CT CERVICAL SPINE POST DISKOGRAM": "IMAGING",
"CT CERVICAL SPINE POST MYELOGRAM": "IMAGING",
"CT CERVICAL SPINE W CONTRAST": "IMAGING",
"CT CERVICAL SPINE WO CONTRAST": "IMAGING",
"CT CERVICAL SPINE WO W CONTRAST": "IMAGING",
"CT CHEST": "IMAGING",
"CT CHEST ABDOMEN": "IMAGING",
"CT CHEST ABDOMEN PELVIS": "IMAGING",
"CT CHEST ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT CHEST ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT CHEST ABDOMEN PELVIS WO CONTRAST": "IMAGING",
"CT CHEST ABDOMEN W CONTRAST": "IMAGING",
"CT CHEST ABDOMEN W WO CONTRAST": "IMAGING",
"CT CHEST ABDOMEN WO CONTRAST": "IMAGING",
"CT CHEST COMBO": "IMAGING",
"CT CHEST CYBER KNIFE": "IMAGING",
"CT CHEST CYBER KNIFE W CONTRAST": "IMAGING",
"CT CHEST CYBER KNIFE W WO CONTRAST": "IMAGING",
"CT CHEST CYBER KNIFE WO CONTRAST": "IMAGING",
"CT CHEST HIGH RESOLUTION": "IMAGING",
"CT CHEST LUNG SCREENING": "IMAGING",
"CT CHEST NO CONTRAST": "IMAGING",
"CT CHEST PE IMAGING": "IMAGING",
"CT CHEST PE IMAGING- 2D": "IMAGING",
"CT CHEST PULEMBOLI W/CONTRAST": "IMAGING",
"CT CHEST W ABDOMEN PELVIS W WO": "IMAGING",
"CT CHEST W ABDOMEN W WO CONTRAST": "IMAGING",
"CT CHEST W ABDOMEN W WO PELVIS W CONTRAST": "IMAGING",
"CT CHEST W CONTRAST": "IMAGING",
"CT CHEST W WO ABDOMEN W CONTRAST": "IMAGING",
"CT CHEST W/CONTRAST": "IMAGING",
"CT CHEST WITH CONTRAST": "IMAGING",
"CT CHEST WO ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT CHEST WO ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT CHEST WO ABDOMEN W WO CONTRAST": "IMAGING",
"CT CHEST WO CONTRAST": "IMAGING",
"CT CHEST WO W CONTRAST": "IMAGING",
"CT CHEST/ABD W/O CONTRAST": "IMAGING",
"CT CHEST/ABD WITH CONTRAST": "IMAGING",
"CT CHEST/ABD/PEL W/CONTRAST": "IMAGING",
"CT CHEST/ABD/PEL W/O CONTRAST": "IMAGING",
"CT CHEST/ABD/PELV NO CONTRAST": "IMAGING",
"CT CHEST/ABD/PELVIS NO CONT": "IMAGING",
"CT CHEST/ABD/PELVIS COMBO": "IMAGING",
"CT CHEST/ABD/PELVIS W/CONTRAST": "IMAGING",
"CT CHEST/ABDOMEN COMBO": "IMAGING",
"CT CHEST/ABDOMEN W/CONTRAST": "IMAGING",
"CT CHEST/ABDOMEN/PELVIS COMBO": "IMAGING",
"CT COLONOGRAPHY": "IMAGING",
"CT COLONOGRAPHY DX W WO CONTRAST": "IMAGING",
"CT COLONOGRAPHY DX WO CONTRAST": "IMAGING",
"CT COLONOGRAPHY SCREENING": "IMAGING",
"CT COLONOSCOPY COLONOGRAPHY": "IMAGING",
"CT COLONOSCOPY DIAG W & WO CONTRAST": "IMAGING",
"CT COLONOSCOPY DIAG/PREPAY": "IMAGING",
"CT COLONOSCOPY DIAGNOSTIC": "IMAGING",
"CT COLONOSCOPY DIAGNOSTIC W OUT CONTRAST": "IMAGING",
"CT COLONOSCOPY SCREEN/PREPAY": "IMAGING",
"CT COLONOSCOPY SCREENING": "IMAGING",
"CT CYSTOGRAM": "IMAGING",
"CT CYSTOGRAM W CONTRAST": "IMAGING",
"CT CYSTOGRAM W WO CONTRAST": "IMAGING",
"CT DISKOGRAM CERVICAL SPINE": "IMAGING",
"CT DISKOGRAM LUMBAR SPINE": "IMAGING",
"CT DISKOGRAM THORACIC SPONE": "IMAGING",
"CT EAR/IAC'S": "IMAGING",
"CT EAR/IAC'S W CONTRAST": "IMAGING",
"CT EAR/IAC'S WO CONTRAST": "IMAGING",
"CT EAR/IAC'S WO W CONTRAST": "IMAGING",
"CT ELBOW LEFT": "IMAGING",
"CT ELBOW RIGHT": "IMAGING",
"CT ELBOW W CONTRAST LEFT": "IMAGING",
"CT ELBOW W CONTRAST RIGHT": "IMAGING",
"CT ELBOW W WO CONTRAST LEFT": "IMAGING",
"CT ELBOW W WO CONTRAST RIGHT": "IMAGING",
"CT ELBOW WO CONTRAST LEFT": "IMAGING",
"CT ELBOW WO CONTRAST RIGHT": "IMAGING",
"CT ENTEROCLYSIS": "IMAGING",
"CT ENTEROCLYSIS ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT ENTEROCLYSIS ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT ENTEROCLYSIS ABDOMEN PELVIS WO CONTRAST": "IMAGING",
"CT ENTEROGRAPHY": "IMAGING",
"CT ENTEROGRAPHY ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT ENTEROGRAPHY ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT ENTEROGRAPHY ABDOMEN PELVIS WO CONTRAST": "IMAGING",
"CT ENTEROGRAPHY ABDOMEN W CONTRAST": "IMAGING",
"CT ENTEROGRAPHY ABDOMEN W WO CONTRAST": "IMAGING",
"CT ENTEROGRAPHY ABDOMEN WO CONTRAST": "IMAGING",
"CT FACIAL BONES": "IMAGING",
"CT FACIAL BONES COMBO": "IMAGING",
"CT FACIAL BONES CONTRAST": "IMAGING",
"CT FACIAL BONES NO CONTRAST": "IMAGING",
"CT FACIAL BONES W CONTRAST": "IMAGING",
"CT FACIAL BONES WO CONTRAST": "IMAGING",
"CT FACIAL BONES WO W CONTRAST": "IMAGING",
"CT FEMUR LEFT": "IMAGING",
"CT FEMUR RIGHT": "IMAGING",
"CT FEMUR W CONTRAST LEFT": "IMAGING",
"CT FEMUR W CONTRAST RIGHT": "IMAGING",
"CT FEMUR W WO CONTRAST LEFT": "IMAGING",
"CT FEMUR W WO CONTRAST RIGHT": "IMAGING",
"CT FEMUR WO CONTRAST LEFT": "IMAGING",
"CT FEMUR WO CONTRAST RIGHT": "IMAGING",
"CT FIDUCIAL MARKER PLACEMENT": "IMAGING",
"CT FOOT LEFT": "IMAGING",
"CT FOOT RIGHT": "IMAGING",
"CT FOOT W CONTRAST LEFT": "IMAGING",
"CT FOOT W CONTRAST RIGHT": "IMAGING",
"CT FOOT W WO CONTRAST LEFT": "IMAGING",
"CT FOOT W WO CONTRAST RIGHT": "IMAGING",
"CT FOOT WO CONTRAST LEFT": "IMAGING",
"CT FOOT WO CONTRAST RIGHT": "IMAGING",
"CT FOR LOCALIZATION": "IMAGING",
"CT FOREARM LEFT": "IMAGING",
"CT FOREARM RIGHT": "IMAGING",
"CT FOREARM W CONTRAST LEFT": "IMAGING",
"CT FOREARM W CONTRAST RIGHT": "IMAGING",
"CT FOREARM W WO CONTRAST LEFT": "IMAGING",
"CT FOREARM W WO CONTRAST RIGHT": "IMAGING",
"CT FOREARM WO CONTRAST LEFT": "IMAGING",
"CT FOREARM WO CONTRAST RIGHT": "IMAGING",
"CT GUIDE FOR TISSUE ABLATION": "IMAGING",
"CT GUIDE PERITONEAL CATHETER DRAINAGE": "IMAGING",
"CT GUIDE RETROPERITONEAL CATHETER DRAINAGE": "IMAGING",
"CT GUIDE SOFT TISSUE CATHETER DRAINAGE": "IMAGING",
"CT GUIDE TRANSRECTAL CATHETER DRAINAGE": "IMAGING",
"CT GUIDE TRANSVAGINAL CATHETER DRAINAGE": "IMAGING",
"CT GUIDE VISCERAL CATHETER DRAINAGE": "IMAGING",
"CT GUIDED CYST ASPIRATION": "IMAGING",
"CT GUIDED DRAINAGE": "IMAGING",
"CT GUIDED NEEDLE PLACEMENT": "IMAGING",
"CT GUIDED PARACENTESIS": "IMAGING",
"CT GUIDED RADIATION THERAPY FIELDS": "IMAGING",
"CT GUIDED STEREO LOCALIZATION": "IMAGING",
"CT GUIDED THORACENTESIS": "IMAGING",
"CT GUIDED TISSUE ABLATION": "IMAGING",
"CT HAND LEFT": "IMAGING",
"CT HAND RIGHT": "IMAGING",
"CT HAND W CONTRAST LEFT": "IMAGING",
"CT HAND W CONTRAST RIGHT": "IMAGING",
"CT HAND W WO CONTRAST LEFT": "IMAGING",
"CT HAND W WO CONTRAST RIGHT": "IMAGING",
"CT HAND WO CONTRAST LEFT": "IMAGING",
"CT HAND WO CONTRAST RIGHT": "IMAGING",
"CT HD COM/CHST/ABD/PEL W/CONT": "IMAGING",
"CT HD COM/NK/CHST/AB/PEL W/CON": "IMAGING",
"CT HD COM/NK/CHST/ABD/PEL W/CONTR": "IMAGING",
"CT HD COMBO/CHST/ABD/PEL W/CON": "IMAGING",
"CT HD/NK/HST/ABD/PEL W/ CON": "IMAGING",
"CT HEAD ABDOMEN PELVIS": "IMAGING",
"CT HEAD AND SINUS STEALTH": "IMAGING",
"CT HEAD AND SINUS STEALTH W CONTRAST": "IMAGING",
"CT HEAD AND SINUS STEALTH W WO CONTRAST": "IMAGING",
"CT HEAD AND SINUS STEALTH WO CONTRAST": "IMAGING",
"CT HEAD BRAIN": "IMAGING",
"CT HEAD CERV/THOR SPINE": "IMAGING",
"CT HEAD CERV/THOR SPINE W CONTRAST": "IMAGING",
"CT HEAD CERV/THOR SPINE W WO CONTRAST": "IMAGING",
"CT HEAD CERV/THOR SPINE WO CONTRAST": "IMAGING",
"CT HEAD CHEST ABDOMEN PELVIS": "IMAGING",
"CT HEAD COMB/POST FOSSA COMBO": "IMAGING",
"CT HEAD COMB/POST FOSSA W/CON": "IMAGING",
"CT HEAD COMBO IAC'S": "IMAGING",
"CT HEAD COMBO/ABD/PEL W/CONT": "IMAGING",
"CT HEAD COMBO/ABD/PEL W/CONTR": "IMAGING",
"CT HEAD COMBO/CHEST W/CONTRAST": "IMAGING",
"CT HEAD COMBO/SINUS": "IMAGING",
"CT HEAD COMBO/SINUS W/O CONTR": "IMAGING",
"CT HEAD CYBER KNIFE": "IMAGING",
"CT HEAD CYBER KNIFE W CONTRAST": "IMAGING",
"CT HEAD CYBER KNIFE W WO CONTRAST": "IMAGING",
"CT HEAD CYBER KNIFE WO CONTRAST": "IMAGING",
"CT HEAD LEVEL 1": "IMAGING",
"CT HEAD NECK CHEST ABDOMEN PELVIS": "IMAGING",
"CT HEAD SINUS": "IMAGING",
"CT HEAD SINUS W CONTRAST": "IMAGING",
"CT HEAD SINUS W WO CONTRAST": "IMAGING",
"CT HEAD SINUS WO CONTRAST": "IMAGING",
"CT HEAD STEALTH": "IMAGING",
"CT HEAD STEALTH W CONTRAST": "IMAGING",
"CT HEAD STEALTH W WO CONTRAST": "IMAGING",
"CT HEAD STEALTH WO CONTRAST": "IMAGING",
"CT HEAD STRYKER": "IMAGING",
"CT HEAD STRYKER W CONTRAST": "IMAGING",
"CT HEAD STRYKER W WO CONTRAST": "IMAGING",
"CT HEAD STRYKER WO CONTRAST": "IMAGING",
"CT HEAD W CONTRAST": "IMAGING",
"CT HEAD W WO CONTRAST": "IMAGING",
"CT HEAD WO CONTRAST": "IMAGING",
"CT HEAD WO W SINUS WO CONTRAST": "IMAGING",
"CT HEAD/ABD/PEL NO CONTRAST": "IMAGING",
"CT HEAD/ABD/PEL W/CONTRAST": "IMAGING",
"CT HEAD/ABD/PEL W/O CONTRAST": "IMAGING",
"CT HEAD/ABD/PELVIS COMBO": "IMAGING",
"CT HEAD/BRAIN COMBO": "IMAGING",
"CT HEAD/BRAIN CONTRAST": "IMAGING",
"CT HEAD/BRAIN NO CONTRAST": "IMAGING",
"CT HEAD/CHEST/ABD/PEL W/O CON": "IMAGING",
"CT HEAD/CHST/ADB/PEL COMBO": "IMAGING",
"CT HEAD/CHT/ADD/PEL W/CONTRAST": "IMAGING",
"CT HEAD/NCK/CHT/ABD/PEL W/O CON": "IMAGING",
"CT HEAD/NECK/CHST/ABD/PEL COMBO": "IMAGING",
"CT HEAD/SINUS COMBO": "IMAGING",
"CT HEAD/SINUS W/ CONTRAST": "IMAGING",
"CT HEAD/SINUS W/O CONTRAST": "IMAGING",
"CT HEART CONGENITAL": "IMAGING",
"CT HEART STRUCTURE": "IMAGING",
"CT HEART W CONTRAST FOR EVAL CONG HEART DISEASE": "IMAGING",
"CT HEART W CONTRAST FOR EVAL OF CARIAC STRUCTURE": "IMAGING",
"CT HEART W O CONT EVAL CORN CALC": "IMAGING",
"CT HEART WO CONTRAST W QUANT EVAL CALCIUM": "IMAGING",
"CT HEEL LEFT": "IMAGING",
"CT HEEL RIGHT": "IMAGING",
"CT HEEL W CONTRAST LEFT": "IMAGING",
"CT HEEL W CONTRAST RIGHT": "IMAGING",
"CT HEEL W WO CONTRAST LEFT": "IMAGING",
"CT HEEL W WO CONTRAST RIGHT": "IMAGING",
"CT HEEL WO CONTRAST LEFT": "IMAGING",
"CT HEEL WO CONTRAST RIGHT": "IMAGING",
"CT HIP LEFT": "IMAGING",
"CT HIP RIGHT": "IMAGING",
"CT HIP W CONTRAST LEFT": "IMAGING",
"CT HIP W CONTRAST RIGHT": "IMAGING",
"CT HIP W WO CONTRAST LEFT": "IMAGING",
"CT HIP W WO CONTRAST RIGHT": "IMAGING",
"CT HIP WO CONTRAST LEFT": "IMAGING",
"CT HIP WO CONTRAST RIGHT": "IMAGING",
"CT HUMERUS LEFT": "IMAGING",
"CT HUMERUS RIGHT": "IMAGING",
"CT HUMERUS W CONTRAST LEFT": "IMAGING",
"CT HUMERUS W CONTRAST RIGHT": "IMAGING",
"CT HUMERUS W WO CONTRAST LEFT": "IMAGING",
"CT HUMERUS W WO CONTRAST RIGHT": "IMAGING",
"CT HUMERUS WO CONTRAST LEFT": "IMAGING",
"CT HUMERUS WO CONTRAST RIGHT": "IMAGING",
"CT IAC'S": "IMAGING",
"CT IAC'S COMBO": "IMAGING",
"CT IAC'S CONTRAST": "IMAGING",
"CT IAC'S NO CONTRAST": "IMAGING",
"CT KNEE LEFT": "IMAGING",
"CT KNEE RIGHT": "IMAGING",
"CT KNEE W CONTRAST LEFT": "IMAGING",
"CT KNEE W CONTRAST RIGHT": "IMAGING",
"CT KNEE W WO CONTRAST LEFT": "IMAGING",
"CT KNEE W WO CONTRAST RIGHT": "IMAGING",
"CT KNEE WO CONTRAST LEFT": "IMAGING",
"CT KNEE WO CONTRAST RIGHT": "IMAGING",
"CT LEFT LOWER EXTREMITY": "IMAGING",
"CT LEFT UPPER EXTREMITY": "IMAGING",
"CT LEG BILATERAL": "IMAGING",
"CT LEG LEFT": "IMAGING",
"CT LEG LENGTHS": "IMAGING",
"CT LEG RIGHT": "IMAGING",
"CT LEG W CONTRAST BILATERAL": "IMAGING",
"CT LEG W CONTRAST LEFT": "IMAGING",
"CT LEG W CONTRAST RIGHT": "IMAGING",
"CT LEG W WO CONTRAST BILATERAL": "IMAGING",
"CT LEG W WO CONTRAST LEFT": "IMAGING",
"CT LEG W WO CONTRAST RIGHT": "IMAGING",
"CT LEG WO CONTRAST BILATERAL": "IMAGING",
"CT LEG WO CONTRAST LEFT": "IMAGING",
"CT LEG WO CONTRAST RIGHT": "IMAGING",
"CT LIMITED STUDY OR FOLLOW UP": "IMAGING",
"CT LOWER EXT COMBO BILAT": "IMAGING",
"CT LOWER EXT COMBO LEFT": "IMAGING",
"CT LOWER EXT COMBO RIGHT": "IMAGING",
"CT LOWER EXT NO CONTRAST BILAT": "IMAGING",
"CT LOWER EXT NO CONTRAST LEFT": "IMAGING",
"CT LOWER EXT NO CONTRAST RIGHT": "IMAGING",
"CT LOWER EXT W/CONTRAST BILAT": "IMAGING",
"CT LOWER EXT W/CONTRAST LEFT": "IMAGING",
"CT LOWER EXT W/CONTRAST RIGHT": "IMAGING",
"CT LOWER EXT WO CONTRAST RIGHT": "IMAGING",
"CT LOWER EXTREMITY BILATERAL": "IMAGING",
"CT LOWER EXTREMITY LEFT": "IMAGING",
"CT LOWER EXTREMITY RIGHT": "IMAGING",
"CT LOWER EXTREMITY W CONTRAST": "IMAGING",
"CT LOWER EXTREMITY W CONTRAST LEFT": "IMAGING",
"CT LOWER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"CT LOWER EXTREMITY W WO CONTRAST": "IMAGING",
"CT LOWER EXTREMITY W WO CONTRAST LEFT": "IMAGING",
"CT LOWER EXTREMITY W WO CONTRAST RIGHT": "IMAGING",
"CT LOWER EXTREMITY WO CONTRAST": "IMAGING",
"CT LOWER EXTREMITY WO CONTRAST LEFT": "IMAGING",
"CT LUMBAR SPINE": "IMAGING",
"CT LUMBAR SPINE COMBO": "IMAGING",
"CT LUMBAR SPINE NO CONTRAST": "IMAGING",
"CT LUMBAR SPINE POST DISKOGRAM": "IMAGING",
"CT LUMBAR SPINE POST MYELOGRAM": "IMAGING",
"CT LUMBAR SPINE W CONTRAST": "IMAGING",
"CT LUMBAR SPINE W/CONTRAST": "IMAGING",
"CT LUMBAR SPINE WO CONTRAST": "IMAGING",
"CT LUMBAR SPINE WO W CONTRAST": "IMAGING",
"CT MANDIBLE": "IMAGING",
"CT MANDIBLE W CONTRAST": "IMAGING",
"CT MANDIBLE WO CONTRAST": "IMAGING",
"CT MANDIBLE WO W CONTRAST": "IMAGING",
"CT MRI BRAIN DONE GT24 HRS": "IMAGING",
"CT NECK CHEST": "IMAGING",
"CT NECK CHEST ABDOMEN": "IMAGING",
"CT NECK CHEST ABDOMEN PELVIS": "IMAGING",
"CT NECK CHEST ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT NECK CHEST ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT NECK CHEST ABDOMEN PELVIS WO CONTRAST": "IMAGING",
"CT NECK CHEST ABDOMEN W CONTRAST": "IMAGING",
"CT NECK CHEST ABDOMEN W WO CONTRAST": "IMAGING",
"CT NECK CHEST ABDOMEN WO CONTRAST": "IMAGING",
"CT NECK CHEST W CONTRAST": "IMAGING",
"CT NECK CHEST W WO CONTRAST": "IMAGING",
"CT NECK CHEST WO CONTRAST": "IMAGING",
"CT NECK SOFT TISSUE": "IMAGING",
"CT NECK SOFT TISSUE W CONTRAST": "IMAGING",
"CT NECK SOFT TISSUE WO CONTRAST": "IMAGING",
"CT NECK SOFT TISSUE WO W CONTRAST": "IMAGING",
"CT NECK TISSUE COMBO": "IMAGING",
"CT NECK TISSUE CONTRAST": "IMAGING",
"CT NECK/CHEST COMBO": "IMAGING",
"CT NECK/CHEST NO CONTRAST": "IMAGING",
"CT NECK/CHEST W/CONTRAST": "IMAGING",
"CT NECK/CHEST W/O CONTRAST": "IMAGING",
"CT NECK/CHEST/ABD/PEL COMBO": "IMAGING",
"CT NECK/CHEST/ABD/PEL NO CONT": "IMAGING",
"CT NECK/CHEST/ABD/PEL W/CONT": "IMAGING",
"CT NECK/CHEST/ABD/PEL W/CONTR": "IMAGING",
"CT NECK/CHEST/ABD/PELVIS COMBO": "IMAGING",
"CT NK/CH/ABD/PLV W/O CONTRAST": "IMAGING",
"CT ORBITS": "IMAGING",
"CT ORBITS COMBO": "IMAGING",
"CT ORBITS CONTRAST": "IMAGING",
"CT ORBITS NO CONTRAST": "IMAGING",
"CT ORBITS W CONTRAST": "IMAGING",
"CT ORBITS WO CONTRAST": "IMAGING",
"CT ORBITS WO W CONTRAST": "IMAGING",
"CT PARATHYROID 4D": "IMAGING",
"CT PARATHYROID 4D W CONTRAST": "IMAGING",
"CT PARATHYROID 4D W WO CONTRAST": "IMAGING",
"CT PARATHYROID 4D WO CONTRAST": "IMAGING",
"CT PELVIS": "IMAGING",
"CT PELVIS CYBER KNIE WO CONTRAST": "IMAGING",
"CT PELVIS CYBER KNIFE": "IMAGING",
"CT PELVIS CYBER KNIFE W CONTRAST": "IMAGING",
"CT PELVIS CYBER KNIFE W WO CONTRAST": "IMAGING",
"CT PELVIS W CONTRAST": "IMAGING",
"CT PELVIS WO CONTRAST": "IMAGING",
"CT PELVIS WO W CONTRAST": "IMAGING",
"CT PROC UNLISTED": "IMAGING",
"CT RAD REVIEW 2ND OPINION": "IMAGING",
"CT RADIOLOGIST REVIEW OF OUTSIDE IMAGES": "IMAGING",
"CT RIGHT LOWER EXTREMITY": "IMAGING",
"CT RIGHT UPPER EXTREMITY": "IMAGING",
"CT SACRUM COCCYX": "IMAGING",
"CT SACRUM/COCCYX": "IMAGING",
"CT SACRUM/COCCYX COMBO": "IMAGING",
"CT SACRUM/COCCYX CONTRAST": "IMAGING",
"CT SACRUM/COCCYX NO CONTRAST": "IMAGING",
"CT SACRUM/COCCYX W CONTRAST": "IMAGING",
"CT SACRUM/COCCYX WO CONTRAST": "IMAGING",
"CT SACRUM/COCCYX WO W CONTRAST": "IMAGING",
"CT SALIVARY GLANDS": "IMAGING",
"CT SALIVARY GLANDS COMBO": "IMAGING",
"CT SALIVARY GLANDS CONTRAST": "IMAGING",
"CT SALIVARY GLANDS NO CONTRAST": "IMAGING",
"CT SALIVARY GLANDS W CONTRAST": "IMAGING",
"CT SALIVARY GLANDS WO CONTRAST": "IMAGING",
"CT SALIVARY GLANDS WO W CONTRAST": "IMAGING",
"CT SCAN BONY PELVIS NO CONT": "IMAGING",
"CT SCAN FACE/SINUS COMBO": "IMAGING",
"CT SCAN FACE/SINUS CONTRAST": "IMAGING",
"CT SCAN FACE/SINUS NO CONTRAST": "IMAGING",
"CT SCAN FOR CYST ASPIRATION": "IMAGING",
"CT SCAN FOR NEEDLE BIOPSY": "IMAGING",
"CT SCAN FOR RADN THERAPY GUIDE": "IMAGING",
"CT SCAN FOR THERAPY GUIDE": "IMAGING",
"CT SCAN OF ABDOMEN": "IMAGING",
"CT SCAN OF ABDOMEN COMBO": "IMAGING",
"CT SCAN OF ABDOMEN CONTRAST": "IMAGING",
"CT SCAN OF NECK TISSUE": "IMAGING",
"CT SCAN OF PELVIS": "IMAGING",
"CT SCAN OF PELVIS COMBO": "IMAGING",
"CT SCAN OF PELVIS CONTRAST": "IMAGING",
"CT SCAN PELVIS COMBO": "IMAGING",
"CT SCAN PELVIS CONTRAST": "IMAGING",
"CT SCAN PELVIS NO CONTRAST": "IMAGING",
"CT SCAN SKULL": "IMAGING",
"CT SCAN SKULL COMBO": "IMAGING",
"CT SCAN SKULL CONTRAST": "IMAGING",
"CT SCAN TEMPORAL BONES COMBO": "IMAGING",
"CT SCANS, RECONSTRUCT OTHER PLANES": "IMAGING",
"CT SELLA": "IMAGING",
"CT SELLA W CONTRAST": "IMAGING",
"CT SELLA WO CONTRAST": "IMAGING",
"CT SELLA WO W CONTRAST": "IMAGING",
"CT SELLA/PITUITARY COMBO": "IMAGING",
"CT SELLA/PITUITARY CONTRAST": "IMAGING",
"CT SELLA/PITUITARY NO CONTRAST": "IMAGING",
"CT SHOULDER LEFT": "IMAGING",
"CT SHOULDER RIGHT": "IMAGING",
"CT SHOULDER W CONTRAST LEFT": "IMAGING",
"CT SHOULDER W CONTRAST RIGHT": "IMAGING",
"CT SHOULDER W WO CONTRAST LEFT": "IMAGING",
"CT SHOULDER W WO CONTRAST RIGHT": "IMAGING",
"CT SHOULDER WO CONTRAST LEFT": "IMAGING",
"CT SHOULDER WO CONTRAST RIGHT": "IMAGING",
"CT SINUS": "IMAGING",
"CT SINUS COMBO": "IMAGING",
"CT SINUS CONTRAST": "IMAGING",
"CT SINUS FUSION PLANNING": "IMAGING",
"CT SINUS FUSION PLANNING W CONTRAST": "IMAGING",
"CT SINUS FUSION PLANNING W WO CONTRAST": "IMAGING",
"CT SINUS FUSION PLANNING WO CONTRAST": "IMAGING",
"CT SINUS INSTATRAK SYSTEM": "IMAGING",
"CT SINUS NO CONTRAST": "IMAGING",
"CT SINUS NO CONTRAST LIMITED": "IMAGING",
"CT SINUS NO CONTRAST LIMT": "IMAGING",
"CT SINUS STEALTH": "IMAGING",
"CT SINUS STEALTH W CONTRAST": "IMAGING",
"CT SINUS STEALTH W WO CONTRAST": "IMAGING",
"CT SINUS STEALTH WO CONTRAST": "IMAGING",
"CT SINUS W CONTRAST": "IMAGING",
"CT SINUS WO CONTRAST": "IMAGING",
"CT SINUS WO W CONTRAST": "IMAGING",
"CT SOFT TISSUE NECK": "IMAGING",
"CT SOFT TISSUE NECK COMBO": "IMAGING",
"CT SOFT TISSUE NECK CONTRAST": "IMAGING",
"CT SOFT TISSUE NECK NO CONT": "IMAGING",
"CT SPINE CYBER KNIFE": "IMAGING",
"CT SPINE CYBER KNIFE CERVICAL W CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE CERVICAL W WO CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE CERVICAL WO CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE LUMBAR W CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE LUMBAR W WO CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE LUMBAR WO CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE THORACIC W CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE THORACIC W WO CONTRAST": "IMAGING",
"CT SPINE CYBER KNIFE THORACIC WO CONTRAST": "IMAGING",
"CT STEREOTACTIC LOCALIZATION": "IMAGING",
"CT STERNOCLAVICULAR JTS": "IMAGING",
"CT TEMPORAL BONES": "IMAGING",
"CT TEMPORAL BONES CONTRAST": "IMAGING",
"CT TEMPORAL BONES NO CONTRAST": "IMAGING",
"CT TEMPORAL BONES W CONTRAST": "IMAGING",
"CT TEMPORAL BONES WO CONTRAST": "IMAGING",
"CT TEMPORAL BONES WO W CONTRAST": "IMAGING",
"CT THORACIC SPINE": "IMAGING",
"CT THORACIC SPINE COMBO": "IMAGING",
"CT THORACIC SPINE NO CONTRAST": "IMAGING",
"CT THORACIC SPINE POST DISKOGRAM": "IMAGING",
"CT THORACIC SPINE POST MYELOGRAM": "IMAGING",
"CT THORACIC SPINE W CONTRAST": "IMAGING",
"CT THORACIC SPINE W/CONTRAST": "IMAGING",
"CT THORACIC SPINE WO CONTRAST": "IMAGING",
"CT THORACIC SPINE WO W CONTRAST": "IMAGING",
"CT TIBIA-FIBULA LEFT": "IMAGING",
"CT TIBIA-FIBULA RIGHT": "IMAGING",
"CT TIBIA-FIBULA W CONTRAST LEFT": "IMAGING",
"CT TIBIA-FIBULA W CONTRAST RIGHT": "IMAGING",
"CT TIBIA-FIBULA W WO CONTRAST LEFT": "IMAGING",
"CT TIBIA-FIBULA W WO CONTRAST RIGHT": "IMAGING",
"CT TIBIA-FIBULA WO CONTRAST LEFT": "IMAGING",
"CT TIBIA-FIBULA WO CONTRAST RIGHT": "IMAGING",
"CT TMJ BILATERAL": "IMAGING",
"CT TMJ BILATERAL W CONTRAST": "IMAGING",
"CT TMJ BILATERAL WO CONTRAST": "IMAGING",
"CT TMJ BILATERAL WO W CONTRAST": "IMAGING",
"CT TRANSPLANT ABDOMEN": "IMAGING",
"CT TRANSPLANT ABDOMEN W CONTRAST": "IMAGING",
"CT TRANSPLANT ABDOMEN W WO CONTRAST": "IMAGING",
"CT TRANSPLANT ABDOMEN WO CONTRAST": "IMAGING",
"CT TRANSPLANT ANGIO ABDOMEN PELVIS": "IMAGING",
"CT TRANSPLANT ANGIOGRAM ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT TRANSPLANT ANGIOGRAM ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT TRANSPLANT CHEST ABD PELVIS": "IMAGING",
"CT TRANSPLANT CHEST ABD PELVIS W CONTRAST": "IMAGING",
"CT TRANSPLANT CHEST ABD PELVIS W WO CONTRAST": "IMAGING",
"CT TRANSPLANT CHEST ABD PELVIS WO CONTRAST": "IMAGING",
"CT TRANSPLANT CHEST W ABDOMEN PELVIS W WO": "IMAGING",
"CT TRANSPLANT CHEST W ABDOMEN W WO PELVIS W CONTRAST": "IMAGING",
"CT TRANSPLANT CHEST WO ABDOMEN PELVIS W CONTRAST": "IMAGING",
"CT TRANSPLANT CHEST WO ABDOMEN PELVIS W WO CONTRAST": "IMAGING",
"CT UNLISTED": "IMAGING",
"CT UPPER EXT COMBO BILATERAL": "IMAGING",
"CT UPPER EXT COMBO LEFT": "IMAGING",
"CT UPPER EXT COMBO RIGHT": "IMAGING",
"CT UPPER EXT CONTRAST BILAT": "IMAGING",
"CT UPPER EXT CONTRAST LEFT": "IMAGING",
"CT UPPER EXT CONTRAST RIGHT": "IMAGING",
"CT UPPER EXT NO CONTRAST BILAT": "IMAGING",
"CT UPPER EXT NO CONTRAST LEFT": "IMAGING",
"CT UPPER EXT NO CONTRAST RIGHT": "IMAGING",
"CT UPPER EXT W WO CONTRAST RIGHT": "IMAGING",
"CT UPPER EXT WO CONTRAST RIGHT": "IMAGING",
"CT UPPER EXTREMITY BILATERAL": "IMAGING",
"CT UPPER EXTREMITY LEFT": "IMAGING",
"CT UPPER EXTREMITY RIGHT": "IMAGING",
"CT UPPER EXTREMITY W CONTRAST": "IMAGING",
"CT UPPER EXTREMITY W CONTRAST LEFT": "IMAGING",
"CT UPPER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"CT UPPER EXTREMITY W WO CONTRAST": "IMAGING",
"CT UPPER EXTREMITY W WO CONTRAST LEFT": "IMAGING",
"CT UPPER EXTREMITY WO CONTRAST": "IMAGING",
"CT UPPER EXTREMITY WO CONTRAST LEFT": "IMAGING",
"CT UROGRAM": "IMAGING",
"CT UROGRAM W CONTRAST": "IMAGING",
"CT UROGRAM W WO CONTRAST": "IMAGING",
"CT UROGRAM WO CONTRAST": "IMAGING",
"CT VENOGRAM ABDOMEN": "IMAGING",
"CT VENOGRAM ABDOMEN W CONTRAST": "IMAGING",
"CT VENOGRAM ABDOMEN W WO CONTRAST": "IMAGING",
"CT WRIST LEFT": "IMAGING",
"CT WRIST RIGHT": "IMAGING",
"CT WRIST W CONTRAST LEFT": "IMAGING",
"CT WRIST W CONTRAST RIGHT": "IMAGING",
"CT WRIST W WO CONTRAST LEFT": "IMAGING",
"CT WRIST W WO CONTRAST RIGHT": "IMAGING",
"CT WRIST WO CONTRAST LEFT": "IMAGING",
"CT WRIST WO CONTRAST RIGHT": "IMAGING",
"CTA CHEST W CONTRAST AND CT ABD PEL W CONTRAST": "IMAGING",
"CTPET LTD,AREA EVAL IMAGING": "IMAGING",
"CTPET SKULL BASE-MIDTHIGH EVAL IMAGE": "IMAGING",
"CTPET WHOLE BODY EVAL IMAGING": "IMAGING",
"CYBERKNIFE 3D CONTOURING": "IMAGING",
"CYTOLOGY NON-GYNECOLOGIC": "PATHOLOGY",
"DELAYED PROX EXTENS ENDOVASC RETHOR AORTA": "IMAGING",
"DEXA BONE DENSITY AXIAL SKELETON": "IMAGING",
"DEXA BONE DENSITY/VERTEBRAL FX": "IMAGING",
"DEXA,BONE DENSITY,APPENDICULR SKELTN": "IMAGING",
"DIAGNOSTIC - AUDIOLOGY": "IMAGING",
"DIAGNOSTIC - CARDIOLOGY": "IMAGING",
"DIAGNOSTIC - NEURO": "IMAGING",
"DIAGNOSTIC - SLEEP": "IMAGING",
"DIAGNOSTIC - UROLOGY": "IMAGING",
"DIAGNOSTIC DIGITAL BREAST TOMOSYNTHESIS UNILATERAL OR BILATERAL": "IMAGING",
"DIAGNOSTIC MAMMOGRAPHY COMPUTER-AIDED DETCJ BI": "IMAGING",
"DIAGNOSTIC MAMMOGRAPHY COMPUTER-AIDED DETCJ UNI": "IMAGING",
"DIGITAL BREAST TOMOSYNTHESIS BILATERAL": "IMAGING",
"DIGITAL BREAST TOMOSYNTHESIS UNILATERAL": "IMAGING",
"DISCOGRAPHY CERV SPINE": "IMAGING",
"DOC PRES/ABSN HMRHG/LESION": "IMAGING",
"DOPPLER COLOR FLOW VELOCITY MAP": "IMAGING",
"DOPPLER ECHO HEART,COMPLETE": "IMAGING",
"DOPPLER VELOCIMETRY FETAL UMBILICAL ARTERY": "IMAGING",
"DOPPLER VELOCIMETRY FETAL UMBILICAL ARTERY MIDDLE": "IMAGING",
"DUAL ENERGY XRAY ABSORPTIOMETRY 1 OR MORE SITES ": "IMAGING",
"DUPLEX SCAN,CAROTID": "IMAGING",
"DUPLEX SCAN,UNILAT,CAROTID": "IMAGING",
"DX MAMMO INCLUDING COMPUTER AIDED DETECTION": "IMAGING",
"DX MAMMO INCLUDING COMPUTER AIDED DETECTION UNILATERAL": "IMAGING",
"DX POST MORTEM IMAGING": "IMAGING",
"DXA BODY COMPOSITION STUDY": "IMAGING",
"EA ADDITIONAL CYST, OTHER BREAST": "IMAGING",
"EA ADDITIONAL CYST, SAME BREAST": "IMAGING",
"EA ADDL CYST, OTHER BREAST": "IMAGING",
"EA ADDL CYST, SAME BREAST": "IMAGING",
"EA ADDL FNA SAME/OTHER BREAST": "IMAGING",
"EA ADDL LESION BX, OTHER BREAST": "IMAGING",
"EA ADDL LESION BX, SAME BREAST": "IMAGING",
"EACH ADDL FNA SAME/OTHER BREAST": "IMAGING",
"EACH ADDL LESION BX, OTHER BREAST": "IMAGING",
"EACH ADDL LESION BX, SAME BREAST": "IMAGING",
"ECHO CONGENITAL": "IMAGING",
"ECHO DOBUTAMINE HEMODYNAMIC": "IMAGING",
"ECHO FETAL": "IMAGING",
"ECHO HEART LIMITED": "IMAGING",
"ECHO HEART REST W/O COLOR FLOW & DOPPLER": "IMAGING",
"ECHO HEART RESTING": "IMAGING",
"ECHO HEART RESTING W DOPPLER & COLOR FLOW": "IMAGING",
"ECHO HEART STRESS": "IMAGING",
"ECHO HEART TRANSESOPH ACQ INTERP": "IMAGING",
"ECHO HEART TRANSESOPHAGEAL": "IMAGING",
"ECHO LIMITED": "IMAGING",
"ECHO M-MODE/2D/DOPPLER (ROUTINE)": "IMAGING",
"ECHO STRESS": "IMAGING",
"ECHO TEE": "IMAGING",
"ECHO TEE OR": "IMAGING",
"ECHO XTHORACIC CONG ANOM COMPLETE": "IMAGING",
"ECHO XTHORACIC CONG ANOM LIMITED": "IMAGING",
"EEG - ROUTINE": "IMAGING",
"EEG AMBULATORY MONITORING 24 HOURS": "IMAGING",
"EEG CEREBRAL SILENCE": "IMAGING",
"EEG CONTINUOUS MONITORING NO VIDEO": "IMAGING",
"EEG ICTAL SPECT MONITORING": "IMAGING",
"EEG MONITORING W VIDEO": "IMAGING",
"EEG PORTABLE": "IMAGING",
"EEG SLEEP DEPRIVED": "IMAGING",
"EGFR MUTATION": "PATHOLOGY",
"ELECTROCARDIOGRAM 12-LEAD": "IMAGING",
"ELECTROCARDIOGRAM 12-LEAD MAGNET": "IMAGING",
"ELECTROCARDIOGRAM SIGNAL AVERAGED": "IMAGING",
"ELECTROCORTICOGRAPHY": "IMAGING",
"ELECTRODE NERVE CONDUCTION": "IMAGING",
"ELECTROPHORESIS REPORT": "PATHOLOGY",
"ELECTRORETINOGRAPHY": "IMAGING",
"EMBOLIZATION UTERINE FIBROID": "IMAGING",
"EMG - ROUTINE": "IMAGING",
"EMU VIDEO MONITORING": "IMAGING",
"EMU VIDEO MONITORING DISCONTINUE": "IMAGING",
"EMU VIDEO MONITORING REQUEST": "IMAGING",
"ENDOCRINE NUCLEAR PROCEDURE": "IMAGING",
"ENDOVASC DIST EXTENS TAA PROSTH, DELAYED": "IMAGING",
"ENDOVASC PROSTH, TAA, EA ADD": "IMAGING",
"ENDOVASC REPAIR THOR AORTA EXCL SUBCLAVIAN": "IMAGING",
"ENDOVASC REPAIR THOR AORTA INCL SUBCLAVIAN": "IMAGING",
"ENDOVASC TAA REINCL SUBCL": "IMAGING",
"ENDOVASC TEMP BALLOON OCCLUS,HEAD/NCK": "IMAGING",
"ENDOVASCULAR REPAIR USING PROSTHESIS OF ABD AORTIC": "IMAGING",
"ENDOVENOUS LASER VEIN ADDON": "IMAGING",
"ENDOVENOUS LASER, 1ST VEIN": "IMAGING",
"EPIDUROGRAPHY,SUPERV/INTERPRET": "IMAGING",
"ESOPHAGEAL MOTILITY STUDY": "IMAGING",
"ESOPHAGRAM": "IMAGING",
"EXTENDED RAS MUTATION ANALYSIS": "PATHOLOGY",
"EYE EXAM DILATED": "IMAGING",
"EYE EXAM NON-DILATED": "IMAGING",
"FETAL AUTOPSY": "PATHOLOGY",
"FETAL MONITORING STRIP": "IMAGING",
"FISH ALK": "PATHOLOGY",
"FISH ALL PANEL INTERPRETATION": "PATHOLOGY",
"FISH ROS1": "PATHOLOGY",
"FL ANKLE INJ PRE CT/MRI ARTHROGRAM LEFT": "IMAGING",
"FL ANKLE INJ PRE CT/MRI ARTHROGRAM RIGHT": "IMAGING",
"FL ARTHROGRAM ANKLE BILATERAL": "IMAGING",
"FL ARTHROGRAM ANKLE LEFT": "IMAGING",
"FL ARTHROGRAM ANKLE RIGHT": "IMAGING",
"FL ARTHROGRAM ELBOW BILATERAL": "IMAGING",
"FL ARTHROGRAM ELBOW LEFT": "IMAGING",
"FL ARTHROGRAM ELBOW RIGHT": "IMAGING",
"FL ARTHROGRAM HIP BILATERAL": "IMAGING",
"FL ARTHROGRAM HIP LEFT": "IMAGING",
"FL ARTHROGRAM HIP RIGHT": "IMAGING",
"FL ARTHROGRAM KNEE BILATERAL": "IMAGING",
"FL ARTHROGRAM KNEE LEFT": "IMAGING",
"FL ARTHROGRAM KNEE RIGHT": "IMAGING",
"FL ARTHROGRAM SHOULDER BILATERAL": "IMAGING",
"FL ARTHROGRAM SHOULDER LEFT": "IMAGING",
"FL ARTHROGRAM SHOULDER RIGHT": "IMAGING",
"FL ARTHROGRAM TMJ LEFT": "IMAGING",
"FL ARTHROGRAM TMJ RIGHT": "IMAGING",
"FL ARTHROGRAM WRIST BILATERAL": "IMAGING",
"FL ARTHROGRAM WRIST LEFT": "IMAGING",
"FL ARTHROGRAM WRIST RIGHT": "IMAGING",
"FL CHEST 4 + VW W FLUOROSCOPY": "IMAGING",
"FL CHEST PA LATERAL W FLUOROSCOPY": "IMAGING",
"FL CHOLANGIOGRAM INTRAOPERATIVE": "IMAGING",
"FL CHOLECYSTOGRAM ORAL": "IMAGING",
"FL CISTERNOGRAM POSITIVE CONTRAST": "IMAGING",
"FL COLON": "IMAGING",
"FL COLON BARIUM ENEMA": "IMAGING",
"FL COLON BARIUM ENEMA W AIR CONTRAST": "IMAGING",
"FL COLON GASTROGRAFIN ENEMA": "IMAGING",
"FL COLON THERAPEUTIC": "IMAGING",
"FL CYSTOGRAM": "IMAGING",
"FL CYSTOGRAM INTRAOPERATIVE": "IMAGING",
"FL DEFOGRAM": "IMAGING",
"FL DISCOGRAM LUMBAR SPINE": "IMAGING",
"FL ELBOW INJ PRE CT/MRI ARTHROGRAM LEFT": "IMAGING",
"FL ELBOW INJ PRE CT/MRI ARTHROGRAM RIGHT": "IMAGING",
"FL ERCP BILIARY AND PANCREATIC": "IMAGING",
"FL ERCP BILIARY ONLY": "IMAGING",
"FL ERCP PANCREAS ONLY": "IMAGING",
"FL ESOPHAGRAM": "IMAGING",
"FL ESOPHOGRAM AND UGI W AIR CONTRAST W KUB": "IMAGING",
"FL ESOPHOGRAM AND UGI W AIR CONTRAST WO KUB": "IMAGING",
"FL ESOPHOGRAM AND UGI W KUB": "IMAGING",
"FL ESOPHOGRAM AND UGI WO KUB": "IMAGING",
"FL ESOPHOGRAM AND UPPER GI": "IMAGING",
"FL EYE DACROCYSTOGRAM BILATERAL": "IMAGING",
"FL EYE DACROCYSTOGRAM LEFT": "IMAGING",
"FL EYE DACROCYSTOGRAM RIGHT": "IMAGING",
"FL FACET INJECTION": "IMAGING",
"FL FALLOPIAN TUBE CATHETERIZATION": "IMAGING",
"FL FISTULA ABSCESS SINUS TRACT": "IMAGING",
"FL FISTULOGRAM ABSCESS SINUS TRACT": "IMAGING",
"FL FLUORO GUIDANCE GI TUBE CHECK": "IMAGING",
"FL FLUORO GUIDE ANKLE ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE ANKLE ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE ANKLE ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE ANKLE ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE ANKLE INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE ANKLE INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE DRAINAGE": "IMAGING",
"FL FLUORO GUIDE ELBOW ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE ELBOW ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE ELBOW ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE ELBOW ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE ELBOW INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE ELBOW INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE FINGER ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE FINGER ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE FINGER ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE FINGER ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE FINGER INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE FINGER INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE FOOT ASIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE FOOT ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE FOOT ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE FOOT ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE FOOT INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE FOOT INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE FOR SPINE INJECT": "IMAGING",
"FL FLUORO GUIDE HAND ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE HAND ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE HAND ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE HAND ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE HAND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE HAND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE HIP ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE HIP ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE HIP ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE HIP ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE HIP INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE HIP INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE KNEE ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE KNEE ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE KNEE ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE KNEE ASPRIATION RIGHT": "IMAGING",
"FL FLUORO GUIDE KNEE INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE KNEE INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE LARGE JOINT INJECTION IN IMAGING DEPT": "IMAGING",
"FL FLUORO GUIDE LOWER EXTREMITY JOINT INJ/ASP": "IMAGING",
"FL FLUORO GUIDE MEDIUM JOINT INJECTION IN IMAGING DEPT": "IMAGING",
"FL FLUORO GUIDE PERCUTANEOUS CATHETER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE PERITONEAL CATHETER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE RETROPERITONEAL CATHETER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT ASPIRATION AND INJECTION BILATERAL": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT ASPIRATION BILATERAL": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT INJ/ASP": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT INJECTION BILATERAL": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE SACROILIAC JOINT INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE SHOULDER ASPIRATIN AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE SHOULDER ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE SHOULDER ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE SHOULDER ASPRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE SHOULDER INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE SHOULDER INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE SMALL JOINT INJECTION IN IMAGING DEPT": "IMAGING",
"FL FLUORO GUIDE SOFT TISSUE CATHETER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE SPINE INJECTION PRE CT MYLEOGRAM": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICAL ASPIRATION AND INJECTION BILATERAL": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR ASPIRATION BILATERAL": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR ASPRIATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR INJECTION BILATERAL": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR JOINT": "IMAGING",
"FL FLUORO GUIDE STERNOCLAVICULAR RIGHT": "IMAGING",
"FL FLUORO GUIDE TOE ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE TOE ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE TOE ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE TOE ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE TOE INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE TOE INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE TRANSRECTAL CATHERTER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE TRANSVAGINAL CATHETER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE UPPER EXTREMITY JOINT INJ / ASP": "IMAGING",
"FL FLUORO GUIDE VISCERAL CATHETER DRAINAGE": "IMAGING",
"FL FLUORO GUIDE WRIST ASPIRATION AND INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE WRIST ASPIRATION AND INJECTION RIGHT": "IMAGING",
"FL FLUORO GUIDE WRIST ASPIRATION LEFT": "IMAGING",
"FL FLUORO GUIDE WRIST ASPIRATION RIGHT": "IMAGING",
"FL FLUORO GUIDE WRIST INJECTION LEFT": "IMAGING",
"FL FLUORO GUIDE WRIST INJECTION RIGHT": "IMAGING",
"FL FLUOROSCOPY BRONCHOSCOPY + REPORT": "IMAGING",
"FL FLUOROSCOPY BRONCHOSCOPY NR": "IMAGING",
"FL FLUOROSCOPY CHOLANGIOGRAM + REPORT": "IMAGING",
"FL FLUOROSCOPY CHOLANGIOGRAM NR": "IMAGING",
"FL FLUOROSCOPY ERCP + REPORT": "IMAGING",
"FL FLUOROSCOPY ERCP NR": "IMAGING",
"FL FLUOROSCOPY ORTHO SURGERY NR": "IMAGING",
"FL FLUOROSCOPY OUTSIDE RADIOLOGY + REPORT": "IMAGING",
"FL FLUOROSCOPY OUTSIDE RADIOLOGY NR": "IMAGING",
"FL FLUOROSCOPY PAIN CLINIC NR": "IMAGING",
"FL FLUOROSCOPY PAIN CLINIC NR NO COUNTER": "IMAGING",
"FL FLUOROSCOPY SURGERY + REPORT": "IMAGING",
"FL FLUOROSCOPY SURGERY NR": "IMAGING",
"FL FLUOROSCOPY SURGERY O ARM + REPORT": "IMAGING",
"FL FLUOROSCOPY UROLOGY + REPORT": "IMAGING",
"FL FLUOROSCOPY UROLOGY + REPORT NO COUNTER": "IMAGING",
"FL FLUOROSCOPY UROLOGY NR": "IMAGING",
"FL FLUOROSCOPY UROLOGY NR NO COUNTER": "IMAGING",
"FL FLUOROSCOPY VIEW ONLY IN IMAGING DEPT": "IMAGING",
"FL GUIDE BACLOFEN INJECTION": "IMAGING",
"FL GUIDE BACLOFEN INJECTION CERVICAL/THORACIC": "IMAGING",
"FL GUIDE BACLOFEN INJECTION LUMBAR": "IMAGING",
"FL GUIDE CHEMOTHERAPY ADMINISTRATION": "IMAGING",
"FL GUIDE FEEDING TUBE PLACEMENT": "IMAGING",
"FL GUIDE FOR VEIN DEVICE": "IMAGING",
"FL GUIDE SURGERY LESS THAN 1 HOUR NR": "IMAGING",
"FL GUIDE SURGERY MORE THAN 1 HOUR NR": "IMAGING",
"FL GUIDED LUMBAR PUNCTURE": "IMAGING",
"FL GUIDED NEEDLE PLACEMENT": "IMAGING",
"FL HIP INJ PRE CT/MRI ARTHROGRAM LEFT": "IMAGING",
"FL HIP INJ PRE CT/MRI ARTHROGRAM RIGHT": "IMAGING",
"FL HYSTEROSALPINGOGRAM": "IMAGING",
"FL KNEE INJ PRE CT/MRI ARTHROGRAM LEFT": "IMAGING",
"FL KNEE INJ PRE CT/MRI ARTHROGRAM RIGHT": "IMAGING",
"FL LAP BAND ADJUSTMENT": "IMAGING",
"FL MYELOGRAM 2 + REGIONS SPINE": "IMAGING",
"FL MYELOGRAM CERVICAL SPINE": "IMAGING",
"FL MYELOGRAM LUMBAR SPINE": "IMAGING",
"FL MYELOGRAM THORACIC SPINE": "IMAGING",
"FL NASAL GASTRIC TUBE PLACEMENT": "IMAGING",
"FL NEPHROSTOGRAM": "IMAGING",
"FL NEPHROSTOGRAM LOOPOGRAM BILATERAL": "IMAGING",
"FL NEPHROSTOGRAM LOOPOGRAM LEFT": "IMAGING",
"FL NEPHROSTOGRAM LOOPOGRAM RIGHT": "IMAGING",
"FL ORTHO OUTSIDE RADIOLOGY NR": "IMAGING",
"FL PACS RECORD NR": "IMAGING",
"FL PACS RECORD REPORTABLE": "IMAGING",
"FL POUCHOGRAM": "IMAGING",
"FL PYELOGRAM IVP W TOMOGRAM": "IMAGING",
"FL PYELOGRAM IVP WO TOMOGRAM": "IMAGING",
"FL RAD REVIEW 2ND OPINION": "IMAGING",
"FL RETROGRADE PYELOGRAM W WO KUB": "IMAGING",
"FL SHOULDER INJ PRE CT/MRI ARTHROGRAM LEFT": "IMAGING",
"FL SHOULDER INJ PRE CT/MRI ARTHROGRAM RIGHT": "IMAGING",
"FL SHUNTOGRAM": "IMAGING",
"FL SHUNTOGRAM PERITONEAL VENOUS": "IMAGING",
"FL SHUNTOGRAM RESERVOIR": "IMAGING",
"FL SIALOGRAM BILATERAL": "IMAGING",
"FL SIALOGRAM LT": "IMAGING",
"FL SIALOGRAM RT": "IMAGING",
"FL SMALL BOWEL ENTEROCLYSIS": "IMAGING",
"FL SMALL BOWEL SERIES": "IMAGING",
"FL SNIFF TEST": "IMAGING",
"FL SPEECH EVALUATION": "IMAGING",
"FL T-TUBE CHOLANGIOGRAM": "IMAGING",
"FL THROAT CERVICAL ESOPHAGRAM": "IMAGING",
"FL TOMOGRAM SINGLE PLANE": "IMAGING",
"FL UGI W AIR CONTRAST W SMALL BOWEL": "IMAGING",
"FL UPPER GI": "IMAGING",
"FL UPPER GI AIR CONTRAST W OR WO KUB AND SMALL BOWEL": "IMAGING",
"FL UPPER GI W AIR CONTRAST W KUB": "IMAGING",
"FL UPPER GI W AIR CONTRAST W KUB W SMALL BOWEL": "IMAGING",
"FL UPPER GI W AIR CONTRAST WO KUB": "IMAGING",
"FL UPPER GI W AIR CONTRAST WO KUB W SMALL BOWEL": "IMAGING",
"FL UPPER GI W KUB": "IMAGING",
"FL UPPER GI W KUB W SMALL BOWEL": "IMAGING",
"FL UPPER GI W OR WO KUB AND SMALL BOWEL": "IMAGING",
"FL UPPER GI WITH SMALL BOWEL": "IMAGING",
"FL UPPER GI WO KUB": "IMAGING",
"FL UPPER GI WO KUB W SMALL BOWEL": "IMAGING",
"FL URETHROCYSTOGRAM": "IMAGING",
"FL UROGRAPHY DRIP W NEPHROTOMOGRAMS": "IMAGING",
"FL VENOGRAM LOWER EXTREMITY BILATERAL": "IMAGING",
"FL VENOGRAM LOWER EXTREMITY LEFT": "IMAGING",
"FL VENOGRAM LOWER EXTREMITY RIGHT": "IMAGING",
"FL VENOGRAM UPPER EXTREMITY BILATERAL": "IMAGING",
"FL VENOGRAM UPPER EXTREMITY LEFT": "IMAGING",
"FL VENOGRAM UPPER EXTREMITY RIGHT": "IMAGING",
"FL VIDEO SWALLOW STUDY": "IMAGING",
"FL VOIDING URETHROCYSTOGRAM": "IMAGING",
"FL WRIST INJ PRE CT/MRI ARTHROGRAM LEFT": "IMAGING",
"FL WRIST INJ PRE CT/MRI ARTHROGRAM RIGHT": "IMAGING",
"FLOW CYTOMETRY BLOOD": "PATHOLOGY",
"FLOW CYTOMETRY BONE MARROW": "PATHOLOGY",
"FLOW CYTOMETRY TISSUE": "PATHOLOGY",
"FLOW INTERPRETATION": "PATHOLOGY",
"FLUORO GUIDANCE CHEST BX": "IMAGING",
"FLUORO GUIDE FOR SPINE INJECT": "IMAGING",
"FLUORO PROC UNLISTED": "IMAGING",
"FLUOROSCOPE EXAM>1 HR EXTENSIVVE": "IMAGING",
"FLUOROSCOPE EXAMINATION": "IMAGING",
"FNA W/ CYTOLOGY": "IMAGING",
"FNA WITH CYTOLOGY": "IMAGING",
"FOLLICULAR STUDY DONE IN OB DEPT": "IMAGING",
"FULL MOUTH X-RAY OF TEETH": "IMAGING",
"GASTRIC EMPTYING IMAGING STUDY WITH SMALL BOWEL TRANSIT": "IMAGING",
"GASTRIC EMPTYING IMG STUDY WITH SMALL BOWEL & COLON TRANSIT MULTI DAYS": "IMAGING",
"GASTRIC EMPTYING STUDY": "IMAGING",
"GASTRIC MUCOSA IMAGING": "IMAGING",
"GASTROESOPHAGEAL REFLUX EXAM": "IMAGING",
"GATED HEART, MULTIPLE": "IMAGING",
"GATED HEART, PLANAR SINGLE": "IMAGING",
"GENETIC COUNSELING": "IMAGING",
"GENETICS": "PATHOLOGY",
"GENETICS INTERPRETATION": "PATHOLOGY",
"GENOMIC MICROARRAY POC": "PATHOLOGY",
"GI ENDOSCOPIC ULTRASOUND": "IMAGING",
"GI IMAGE INTRALUMINAL ESOPHAGUS": "IMAGING",
"GI IMAGE INTRALUMINAL THRU ILEUM": "IMAGING",
"GI NUCLEAR PROCEDURE UNLISTED": "IMAGING",
"GI PROTEIN LOSS EXAM": "IMAGING",
"GU NUCLEAR EXAM UNLISTED": "IMAGING",
"HEART FIRST PASS ADD-ON": "IMAGING",
"HEART FIRST PASS MULTIPLE,PLANAR": "IMAGING",
"HEART FIRST PASS SINGLE,PLANAR": "IMAGING",
"HEART FUNCTION, (ADD-ON)": "IMAGING",
"HEART IMAGE (PET) MULTIPLE": "IMAGING",
"HEART IMAGE (PET) SINGLE": "IMAGING",
"HEART INFARCT IMAGE": "IMAGING",
"HEART INFARCT IMAGE SPECT": "IMAGING",
"HEART INFARCT IMAGE W EF": "IMAGING",
"HEART MUSCLE IMAGING (PET)": "IMAGING",
"HEART WALL MOTION (ADD-ON)": "IMAGING",
"HEMATOPOETIC NUCLEAR THERAPY": "IMAGING",
"HEPATOBILIARY NM (HIDA)": "IMAGING",
"HEPATOBILIARY SYS IMAGING INCL GALLBLADD W PHARM INTERVE": "IMAGING",
"HEPATOBILIARY SYSTEM IMAGING INCL GALLBLADDER WHEN PRESE": "IMAGING",
"HI INTEN BRACHYRX 1-4 SOURCE": "IMAGING",
"HI INTEN BRACHYRX 5-8 SOURCE": "IMAGING",
"HI INTEN BRACHYRX 9-12 SOURCE": "IMAGING",
"HI INTEN BRACHYRX >12 SOURCE": "IMAGING",
"HIGH DOSE RATE BRACHYTHERAPY 1 CHANNEL": "IMAGING",
"HIGH DOSE RATE BRACHYTHERAPY 2-12 CHANNELS": "IMAGING",
"HIGH DOSE RATE BRACHYTHERAPY OVER 12 CHANNELS": "IMAGING",
"HISTOLOGY SLIDE PROCESSING ONLY": "PATHOLOGY",
"HPV GENOTYPING 16 18/45": "PATHOLOGY",
"HPV,HIGH RISK": "PATHOLOGY",
"HYPERTHERMIA EXTERN RX DEEP": "IMAGING",
"HYPERTHERMIA EXTERN RX SUPERF": "IMAGING",
"HYPERTHERMIA INTERN =<5 APPL": "IMAGING",
"HYPERTHERMIA INTERN >5 APPL": "IMAGING",
"HYPERTHERMIA RX INTRACAV PROBE": "IMAGING",
"HYPERTHYROID TX RADIOPHARM ORAL": "IMAGING",
"IFE WITH IGG IGA IGM INTERPRETATION": "PATHOLOGY",
"IMAGE GUIDE PLACE OF METALLIC TISSUE MARKER": "IMAGING",
"IMAGE POST PROCESS INDEPENDENT WS": "IMAGING",
"IMAGE TEST REF CAROT DIAM": "IMAGING",
"IMAGING": "IMAGING",
"IMAGING-BONE DENSITY": "IMAGING",
"IMAGING-CT": "IMAGING",
"IMAGING-DIAGNOSTIC": "IMAGING",
"IMAGING-INTERVENTIONAL": "IMAGING",
"IMAGING-MAMMO": "IMAGING",
"IMAGING-MRI": "IMAGING",
"IMAGING-NUC MED": "IMAGING",
"IMAGING-US": "IMAGING",
"IMAGING-VASCULAR": "IMAGING",
"IMMUNOASSAY TUMOR ANTIGEN": "IMAGING",
"IMMUNOFIXATION URINE INTERPRETATION": "PATHOLOGY",
"IMPLANT TISSUE MARKERS LUNG": "IMAGING",
"IMPLANT WIRELESS PRESS SENSOR STUDY ANEURYSM SAC": "IMAGING",
"INFUSE RADIOACTIVE MATERIALS": "IMAGING",
"INJ PROC FOR RADIOPHARMA LOCALIZATION BY NON-IMAG PROBE STUDY IV": "IMAGING",
"INJ SINUS TRACT,DIAG,SINOGRAM": "IMAGING",
"INJECTION GADOBUTROL 0.1 ML": "IMAGING",
"INJECTION RX EXTREMITY PSEUDOANEURYSM": "IMAGING",
"INJECTION,THERAP/PROPH/DIAGNOST, INTRA-ARTERIAL": "IMAGING",
"INSERT CECOSTOMY/OTHER COLONIC TUBE PERCUTANEOUS": "IMAGING",
"INSERT GASTROSTOMY TUBE PERCUTANEOUS": "IMAGING",
"INSERT PICC W/ SUB-Q PORT": "IMAGING",
"INSERT PICC W/ SUB-Q PORT <5 Y/O": "IMAGING",
"INSERT PICC W/O SUB-Q PORT <5 Y/O": "IMAGING",
"INSERT SUBQ EXTENSION INTRAPERITONEAL CATH": "IMAGING",
"INSERT TRANSVEN INTRAHEP PORTOSYS SHUNT": "IMAGING",
"INSERT TUNNELED CV CATH W 2 ACCESS SITES, W/ PUMP OR PORT": "IMAGING",
"INSERT TUNNELED CV CATH W 2 ACCESS SITES, W/O PUMP OR PORT": "IMAGING",
"INSERT TUNNELED CV CATH W/O PORT OR PUMP < 5 Y/O": "IMAGING",
"INSERT TUNNELED CV CATH WITH PORT <5 Y/O": "IMAGING",
"INSERT TUNNELED CV CATH WITH PUMP": "IMAGING",
"INTERSTI RADIOELEM APPL COMPLX": "IMAGING",
"INTERSTI RADIOELEM APPL INTERM": "IMAGING",
"INTERSTI RADIOELEM APPL SIMPLE": "IMAGING",
"INTERSTITIAL NUCLEAR THERAPY": "IMAGING",
"INTRACAV RADIOELEM APPL COMPLX": "IMAGING",
"INTRACAV RADIOELEM APPL INTERM": "IMAGING",
"INTRACAVITARY NUCLEAR TREATMENT": "IMAGING",
"INTRACAVITY RADIATION SOURCE APPLICATION": "IMAGING",
"INTRACRANIAL BALLOON ANGIOPLASTY": "IMAGING",
"INTRACRANIAL BALLOON ANGIOPLSTY W/STENT": "IMAGING",
"INTRAOPERATIVE RADIATION TREATMENT MANAGEMENT": "IMAGING",
"INTRAVASCULAR NUCLEAR THERAPY": "IMAGING",
"INTRAVASCULAR OPTICAL COHERENCE TOMOGRAPHY INC IMAG ": "IMAGING",
"IR AAA STENT GRAFT PLACEMENT": "IMAGING",
"IR ABDOMINAL/RETROPERITONEAL BIOPSY": "IMAGING",
"IR ADRENAL VEIN SAMPLING": "IMAGING",
"IR ADRENAL VENOGRAM": "IMAGING",
"IR ANGIOGRAM EXTREMITY LEFT": "IMAGING",
"IR ANGIOGRAM EXTREMITY RIGHT": "IMAGING",
"IR AORTIC ARCH ANGIOGRAM": "IMAGING",
"IR AORTOGRAM W BILAT UNILAT RUN-OFF OF LOWER EXT *W INTERVENTION": "IMAGING",
"IR ARTHROGRAM": "IMAGING",
"IR AV GRAFT/FISTULA (FISTULAGRAM W/ INTERVENTION)": "IMAGING",
"IR BACLOFEN PUMP CHECK": "IMAGING",
"IR BILIARY DRAIN EXCHANGE": "IMAGING",
"IR BILIARY STENT PLACEMENT": "IMAGING",
"IR BILIARY STONE REMOVAL": "IMAGING",
"IR BILIARY TUBE": "IMAGING",
"IR BILIARY/NEPHROSTOMY TUBE PLACEMENTS/CHECKS/EXCHANGES": "IMAGING",
"IR BLOOD PATCH": "IMAGING",
"IR CAROTID ANGIOGRAM *W/INTERVENTION": "IMAGING",
"IR CAROTID STENT": "IMAGING",
"IR CAROTID STENT NON RADIOLOGIST": "IMAGING",
"IR CAT SCAN GUIDED LIVER/LUNG BIOPSIES (ALSO ULTRASOUND GUIDANCE)": "IMAGING",
"IR CATHETER STRIPPING": "IMAGING",
"IR CENTRAL LINE": "IMAGING",
"IR CENTRAL LINE EXCHANGE": "IMAGING",
"IR CENTRAL VENOUS LINE INJECTION": "IMAGING",
"IR CEREBRAL ANGIOGRAM": "IMAGING",
"IR CEREBRAL COILING": "IMAGING",
"IR CEREBRAL COILING NON RADIOLOGIST": "IMAGING",
"IR CEREBRAL EMBOLIZATION": "IMAGING",
"IR CEREBRAL EMBOLIZATION NON RADIOLOGIST": "IMAGING",
"IR CEREBRAL NON RADIOLOGIST": "IMAGING",
"IR CHEMOEMBOLIZATION (TACE)": "IMAGING",
"IR CHEST TUBE AND/OR DRAINAGE CATH PLMNT FOR PTX, PLEURAL EFFUSION": "IMAGING",
"IR CHOLANGIOGRAM VIA T-TUBE": "IMAGING",
"IR CHOLECYSTOSTOMY EXCHANGE": "IMAGING",
"IR CONSULT IP": "IMAGING",
"IR CONSULT OP SERV COMPREHENSIVE ACUITY-EST PT": "IMAGING",
"IR CONSULT OP SERV COMPREHENSIVE ACUITY-NEW PT": "IMAGING",
"IR CONSULT OP SERV HIGH ACUITY-EST PT": "IMAGING",
"IR CONSULT OP SERV HIGH ACUITY-NEW PT": "IMAGING",
"IR CONSULT OP SERV LOW ACUITY EST PT": "IMAGING",
"IR CONSULT OP SERV LOW ACUITY NEW PT": "IMAGING",
"IR CONSULT OP SERV MINOR ACUITY EST PT": "IMAGING",
"IR CONSULT OP SERV MINOR ACUITY NEW PT": "IMAGING",
"IR CONSULT OP SERV MOD ACUITY EST PT": "IMAGING",
"IR CONSULT OP SERV MOD ACUITY NEW PT": "IMAGING",
"IR CONSULT SERVICE TO IR": "IMAGING",
"IR CRYO-ABLATION": "IMAGING",
"IR DIALYSIS CATHETER": "IMAGING",
"IR DIALYSIS SHUNT": "IMAGING",
"IR DISC BIOPSY": "IMAGING",
"IR DISCOGRAM LUMBAR SPINE": "IMAGING",
"IR DRAIN EXCHANGE": "IMAGING",
"IR DRESSING CHANGE": "IMAGING",
"IR EMBOLIZATION": "IMAGING",
"IR ENDOVASCULAR REPAIR OF AAA (STENT GRAFT)": "IMAGING",
"IR ENDOVENOUS LASER ABLATION": "IMAGING",
"IR EPIDURAL INJECTION": "IMAGING",
"IR ERCP": "IMAGING",
"IR EVLA": "IMAGING",
"IR FIDUCIAL MARKER PLACEMENT": "IMAGING",
"IR FOLLOW UP VISIT": "IMAGING",
"IR FOLLOW UP VISIT IP": "IMAGING",
"IR FOLLOW UP VISIT OP SERV LOW ACUITY EST PT": "IMAGING",
"IR FOLLOW UP VISIT OP SERV LOW ACUITY NEW PT": "IMAGING",
"IR FOLLOW UP VISIT OP SERV MINOR ACUITY EST PT": "IMAGING",
"IR FOLLOW UP VISIT OP SERV MINOR ACUITY NEW PT": "IMAGING",
"IR FOLLOW UP VISIT OP SERV MOD ACUITY EST PT": "IMAGING",
"IR FOLLOW UP VISIT OP SERV MOD ACUITY NEW PT": "IMAGING",
"IR FOREIGN BODY REMOVAL": "IMAGING",
"IR G-TUBE CONVERSION": "IMAGING",
"IR G-TUBE EXCHANGE": "IMAGING",
"IR GAMMA KNIFE ARTERIOGRAM NON RADIOLOGIST": "IMAGING",
"IR GASTROJEJUNOSTOMY TUBE": "IMAGING",
"IR GASTROSTOMY TUBE": "IMAGING",
"IR GASTROSTOMY/GASTROJEJUNOSTOMY PLACEMENT/CHECKS/EXCHANGES": "IMAGING",
"IR GENERAL EMBOLIZATIONS (COILS, BEADS, ETC.)": "IMAGING",
"IR GUIDED BIOPSY": "IMAGING",
"IR HEPATIC VENOGRAM": "IMAGING",
"IR IMPLANTABLE PORT VEIN ACCESS": "IMAGING",
"IR INFERIOR VENA CAVA (IVC) FILTER": "IMAGING",
"IR INFERIOR VENACAVAGRAM": "IMAGING",
"IR INTRATHECAL INJECTION": "IMAGING",
"IR INTRAVASCULAR ULTRASOUND": "IMAGING",
"IR IVC REMOVAL": "IMAGING",
"IR J-TUBE EXCHANGE": "IMAGING",
"IR J-TUBE PLACEMENT": "IMAGING",
"IR JEJUNOSTOMY TUBE": "IMAGING",
"IR JOINT INJECTION/ASPIRATION": "IMAGING",
"IR KIDNEY BIOPSY": "IMAGING",
"IR KYPHOPLASTY": "IMAGING",
"IR LIVER BIOPSY": "IMAGING",
"IR LUMBAR PUNCTURES/INTRATHECAL INJECTIONS": "IMAGING",
"IR LUNG BIOPSY": "IMAGING",
"IR LYMPH NODE/THYROID BIOPSY": "IMAGING",
"IR MAA EMBOLIZATION": "IMAGING",
"IR MEDIPORT REMOVAL": "IMAGING",
"IR MEDIPORT REVISION": "IMAGING",
"IR MEDIPORT SITE CHECK": "IMAGING",
"IR MESENTERIC ANGIOGRAM *W/INTERVENTION": "IMAGING",
"IR MICROWAVE ABLATION": "IMAGING",
"IR MISC DRAINAGE PROCEDURE": "IMAGING",
"IR MUSCLE BIOPSY": "IMAGING",
"IR MYELOGRAM": "IMAGING",
"IR N-G TUBE": "IMAGING",
"IR N-G TUBE PLACEMENT": "IMAGING",
"IR NEPHROSTOGRAM": "IMAGING",
"IR NEPHROSTOMY TUBE": "IMAGING",
"IR NEPHROSTOMY TUBE PLACEMENT": "IMAGING",
"IR PANCREATIC BIOPSY": "IMAGING",
"IR PANCREATIC PSEUDO CYST DRAIN": "IMAGING",
"IR PARACENTESIS": "IMAGING",
"IR PERCUTANEOUS NEPHROSTOMY TUBE PLACEMENT (UNI/BILAT)": "IMAGING",
"IR PERCUTANEOUS TRANSHEPATIC CHOLANGIOGRAM (PTC) *W/INTERVENTION": "IMAGING",
"IR PETROSAL VEIN SAMPLING": "IMAGING",
"IR PHERESIS CATHETER EXCHANGE": "IMAGING",
"IR PHERESIS CATHETER PLACEMENT": "IMAGING",
"IR PHLEBECTOMY": "IMAGING",
"IR PICC": "IMAGING",
"IR PICC LINE EXCHANGE": "IMAGING",
"IR PLEURX CATHETER PLACEMENT": "IMAGING",
"IR PORTAL VEIN EMBOLIZATION (PVE) *W/INTERVENTION": "IMAGING",
"IR PORTAL VENOGRAM": "IMAGING",
"IR PULMONARY ANGIOGRAM *W/INTERVENTION": "IMAGING",
"IR RAD REVIEW 2ND OPINION": "IMAGING",
"IR RADIOFREQ ABLATION (RFA) SOFT TISSUE TUMORS (LIVER, LUNG & RENAL)": "IMAGING",
"IR RADIOFREQUENCY ABLATION": "IMAGING",
"IR RADIOLOGIST REVIEW OF OUTSIDE IMAGES ": "IMAGING",
"IR RENAL ANGIOGRAM *W/INTERVENTION": "IMAGING",
"IR RENAL CYST ASPIRATION": "IMAGING",
"IR RENAL VENOGRAM": "IMAGING",
"IR RENIN VEIN SAMPLING": "IMAGING",
"IR SACROPLASTY": "IMAGING",
"IR SCLEROTHERAPY": "IMAGING",
"IR SHUNTOGRAM NON VASCULAR": "IMAGING",
"IR SIALOGRAM": "IMAGING",
"IR SINOGRAM": "IMAGING",
"IR SIR-SPHERE EMBOLIZATION": "IMAGING",
"IR SPINAL ANGIO": "IMAGING",
"IR SPLENOPORTOGRAPHY": "IMAGING",
"IR SUBCLAVIAN STENT": "IMAGING",
"IR SUPERIOR VENACAVAGRAM": "IMAGING",
"IR SUPRAPUBIC CATHETER PLACEMENT": "IMAGING",
"IR T-FASTENER REMOVAL": "IMAGING",
"IR TEMPORARY DIALYSIS CATHETER": "IMAGING",
"IR THERASPHERE EMBOLIZATION": "IMAGING",
"IR THORACENTESIS": "IMAGING",
"IR THORACIC ANGIO": "IMAGING",
"IR THROMBECTOMY": "IMAGING",
"IR THROMBIN INJECTION": "IMAGING",
"IR THROMBOLYSIS THERAPY": "IMAGING",
"IR TIPSS REVISON": "IMAGING",
"IR TRANSCATHETER BIOPSY": "IMAGING",
"IR TRANSCATHETER THERAPY": "IMAGING",
"IR TRANSJUG INTRAHEPATIC PORTOSYSTEMIC SHNT PLCMNT (TIPS) AND/OR RVSNS": "IMAGING",
"IR TRANSJUGULAR LIVER BIOPSY": "IMAGING",
"IR TRIGEMINAL NEUROLYSIS": "IMAGING",
"IR TUNNELED CATHETER EXCHANGE": "IMAGING",
"IR TUNNELED CATHETER REMOVAL": "IMAGING",
"IR ULTRAFILTRATION CATHETER": "IMAGING",
"IR ULTRASOUND ABDOMEN LIMITED": "IMAGING",
"IR ULTRASOUND CHEST LIMITED": "IMAGING",
"IR UNLISTED": "IMAGING",
"IR UPPER EXTREMITY ANGIO": "IMAGING",
"IR UPPER EXTREMITY ANGIO BILATERAL": "IMAGING",
"IR UPPER EXTREMITY VENOGRAM": "IMAGING",
"IR URETERAL/NEPHRO STENT PLACEMENT": "IMAGING",
"IR US GUIDE IV START": "IMAGING",
"IR UTERINE ARTERY/FIBROID EMBOLIZATION (UAE/UFE) *W/INTERVENTION": "IMAGING",
"IR VARICOCELE EMBOLIZATION": "IMAGING",
"IR VENACAVAGRAM": "IMAGING",
"IR VENOGRAM": "IMAGING",
"IR VERTEBROPLASTY": "IMAGING",
"IR VISCERAL ANGIO": "IMAGING",
"IR WADA INJECTION": "IMAGING",
"IR WHITAKER TEST": "IMAGING",
"IRON ABSORPTION EXAM": "IMAGING",
"JOINT SURVEY SINGLE VIEW 2 OR MORE JOINTS": "IMAGING",
"JOINT(S) SURVEY, SINGLE FILM": "IMAGING",
"JOINTS SURVEY SINGLE FILM": "IMAGING",
"KIDNEY FUNCTION W/INTERVENT": "IMAGING",
"KIDNEY TRANSPLANT EVALUATION": "IMAGING",
"KRAS MUTATION": "PATHOLOGY",
"KUB WITH OBLIQUES": "IMAGING",
"LAB": "IMAGING",
"LEVEEN/SHUNT PATENCY EXAM": "IMAGING",
"LIVER & SPLEEN IMAGE, FLOW": "IMAGING",
"LIVER AND SPLEEN IMAGING": "IMAGING",
"LIVER FUNCTION STUDY": "IMAGING",
"LIVER IMAGE (3-D) W/FLOW": "IMAGING",
"LIVER IMAGING": "IMAGING",
"LIVER IMAGING (SPECT)": "IMAGING",
"LIVER IMAGING WITH FLOW": "IMAGING",
"LIVER IMMUNE PROFILE INTERPRETATION": "PATHOLOGY",
"LOW DOSE COMPUTED TOMOGRAPHY FOR LUNG CANCER SCREENING": "IMAGING",
"LOW DOSE CT SCAN LDCT FOR LUNG CANCER SCREENING": "IMAGING",
"LUNG DIFFERENTIAL FUNCTION": "IMAGING",
"LUNG SCAN PERFUSION": "IMAGING",
"LUNG SCAN VENTILLATION": "IMAGING",
"LUNG V/Q IMAGE SINGLE BREATH": "IMAGING",
"LUNG V/Q IMAGING,REBREATH/WASHOUT": "IMAGING",
"LYMPH SYSTEM IMAGING": "IMAGING",
"LYMPHANGIO ABD/PELV BILAT": "IMAGING",
"LYMPHANGIO ABD/PELV UNILAT": "IMAGING",
"LYMPHANGIO EXTREM BILAT": "IMAGING",
"LYMPHANGIO EXTREM UNILAT": "IMAGING",
"MAGNETIC IMAGE, BONE MARROW": "IMAGING",
"MAGNETIC RESONANCE IMAGING BRAIN FUNCTIONAL MRI": "IMAGING",
"MAGNETIC RESONANCE IMAGING FETAL INC PLACENTAL & MATERNAL PELVIC IMG SINGLE OR FIRST GESTATION": "IMAGING",
"MAGNETIC RESONANCE IMG FETAL INC PLACEN & MATERN PELV IMG EA ADDL GEST": "IMAGING",
"MAMM0 DIAGNOSTIC BILATERAL": "IMAGING",
"MAMMO ASSESS BENGN DOCD": "IMAGING",
"MAMMO ASSESS NEGATIVE DOCD": "IMAGING",
"MAMMO ASSESS SUSP, DOCD": "IMAGING",
"MAMMO BREAST BIOPSY PERFORMED EXTERNAL BILATERAL": "IMAGING",
"MAMMO BREAST BIOPSY PERFORMED EXTERNAL LEFT": "IMAGING",
"MAMMO BREAST BIOPSY PERFORMED EXTERNALLY": "IMAGING",
"MAMMO BREAST BIPOSY PERFORMED EXTERNAL RIGHT": "IMAGING",
"MAMMO BREAST SPECIMEN IMAGE": "IMAGING",
"MAMMO CONSULTATION": "IMAGING",
"MAMMO CONSULTATION BILATERAL": "IMAGING",
"MAMMO CONSULTATION LEFT": "IMAGING",
"MAMMO CONSULTATION RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG AUGMENTED WITH CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG AUGMENTED WITH CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG AUGMENTED WITH CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG AUGMENTED WO CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG AUGMENTED WO CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG AUGMENTED WO CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG WITH CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG WITH CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG WITH CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG WO CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG WO CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC ANALOG WO CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC AUGMENTED BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC AUGMENTED LEFT": "IMAGING",
"MAMMO DIAGNOSTIC AUGMENTED RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL AUGMENTED WITH CAD BILAT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL AUGMENTED WITH CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL AUGMENTED WITH CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL AUGMENTED WO CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL AUGMENTED WO CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL AUGMENTED WO CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL WITH CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL WITH CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL WITH CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL WO CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL WO CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC DIGITAL WO CAD RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC LEFT": "IMAGING",
"MAMMO DIAGNOSTIC RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO AUGMENTED BILAT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO AUGMENTED BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO AUGMENTED LEFT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO AUGMENTED RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO LEFT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO W CAD AUGMENTED BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO W CAD AUGMENTED LEFT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO W CAD AUGMENTED RIGHT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO W CAD BILATERAL": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO W CAD LEFT": "IMAGING",
"MAMMO DIAGNOSTIC W TOMO W CAD RIGHT": "IMAGING",
"MAMMO GALACTOGRAM MULTIPLE DUCTS": "IMAGING",
"MAMMO GALACTOGRAM MULTIPLE DUCTS BILATERAL": "IMAGING",
"MAMMO GALACTOGRAM MULTIPLE DUCTS LEFT": "IMAGING",
"MAMMO GALACTOGRAM MULTIPLE DUCTS RIGHT": "IMAGING",
"MAMMO GALACTOGRAM SINGLE DUCT": "IMAGING",
"MAMMO GALACTOGRAM SINGLE DUCT BILATERAL": "IMAGING",
"MAMMO GALACTOGRAM SINGLE DUCT LEFT": "IMAGING",
"MAMMO GALACTOGRAM SINGLE DUCT RIGHT": "IMAGING",
"MAMMO GUIDE BRST LESION ASP BX WIRE LOC": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION 2 LESIONS BILATERAL": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION 2 LESIONS LEFT": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION 2 LESIONS RIGHT": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION BILATERAL": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION SINGLE LESION BILATERAL": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION SINGLE LESION LEFT": "IMAGING",
"MAMMO GUIDE NEEDLE LOCALIZATION SINGLE LESION RIGHT": "IMAGING",
"MAMMO GUIDED BRST LESION ASP/BX/WIRE LOC": "IMAGING",
"MAMMO INTACT BIOPSY LEFT": "IMAGING",
"MAMMO INTACT BIOPSY RIGHT": "IMAGING",
"MAMMO INTACT STEREOTACTIC BIOPSY 2 LESION LEFT": "IMAGING",
"MAMMO INTACT STEREOTACTIC BIOPSY 2 LESION RIGHT": "IMAGING",
"MAMMO INTACT STEREOTACTIC BIOPSY SINGLE LESION LEFT": "IMAGING",
"MAMMO INTACT STEREOTACTIC BIOPSY SINGLE LESION RIGHT": "IMAGING",
"MAMMO NEEDLE BIOPSY SPECIMEN NON-SURGICAL": "IMAGING",
"MAMMO NEEDLE BX SPECIMEN NON-SURGICAL LEFT": "IMAGING",
"MAMMO NEEDLE BX SPECIMEN NON-SURGICAL RIGHT": "IMAGING",
"MAMMO NEEDLE LOCALIZATION LEFT": "IMAGING",
"MAMMO NEEDLE LOCALIZATION RIGHT": "IMAGING",
"MAMMO PROBABLY BENGN DOCD": "IMAGING",
"MAMMO RAD REVIEW 2ND OPINION": "IMAGING",
"MAMMO RADIOLOGIST REVIEW OF OUTSIDE IMAGES": "IMAGING",
"MAMMO SCREENING ANALOG AUGMENTED WITH CAD BILATERAL": "IMAGING",
"MAMMO SCREENING ANALOG AUGMENTED WITH CAD LEFT": "IMAGING",
"MAMMO SCREENING ANALOG AUGMENTED WITH CAD RIGHT": "IMAGING",
"MAMMO SCREENING ANALOG AUGMENTED WO CAD BILATERAL": "IMAGING",
"MAMMO SCREENING ANALOG AUGMENTED WO CAD LEFT": "IMAGING",
"MAMMO SCREENING ANALOG AUGMENTED WO CAD RIGHT": "IMAGING",
"MAMMO SCREENING ANALOG WITH CAD BILATERAL": "IMAGING",
"MAMMO SCREENING ANALOG WITH CAD LEFT": "IMAGING",
"MAMMO SCREENING ANALOG WITH CAD RIGHT": "IMAGING",
"MAMMO SCREENING ANALOG WO CAD BILATERAL": "IMAGING",
"MAMMO SCREENING ANALOG WO CAD LEFT": "IMAGING",
"MAMMO SCREENING ANALOG WO CAD RIGHT": "IMAGING",
"MAMMO SCREENING AUGMENTED BILATERAL": "IMAGING",
"MAMMO SCREENING AUGMENTED LEFT": "IMAGING",
"MAMMO SCREENING AUGMENTED RIGHT": "IMAGING",
"MAMMO SCREENING BILATERAL": "IMAGING",
"MAMMO SCREENING DIGITAL AUGMENTED WITH CAD BILATERAL": "IMAGING",
"MAMMO SCREENING DIGITAL AUGMENTED WITH CAD LEFT": "IMAGING",
"MAMMO SCREENING DIGITAL AUGMENTED WITH CAD RIGHT": "IMAGING",
"MAMMO SCREENING DIGITAL AUGMENTED WO CAD BILATERAL": "IMAGING",
"MAMMO SCREENING DIGITAL AUGMENTED WO CAD LEFT": "IMAGING",
"MAMMO SCREENING DIGITAL AUGMENTED WO CAD RIGHT": "IMAGING",
"MAMMO SCREENING DIGITAL WITH CAD BILATERAL": "IMAGING",
"MAMMO SCREENING DIGITAL WITH CAD LEFT": "IMAGING",
"MAMMO SCREENING DIGITAL WITH CAD RIGHT": "IMAGING",
"MAMMO SCREENING DIGITAL WO CAD BILATERAL": "IMAGING",
"MAMMO SCREENING DIGITAL WO CAD LEFT": "IMAGING",
"MAMMO SCREENING DIGITAL WO CAD RIGHT": "IMAGING",
"MAMMO SCREENING LEFT": "IMAGING",
"MAMMO SCREENING RIGHT": "IMAGING",
"MAMMO SCREENING W TOMO AUGMENTED BILATERAL": "IMAGING",
"MAMMO SCREENING W TOMO AUGMENTED LEFT": "IMAGING",
"MAMMO SCREENING W TOMO AUGMENTED RIGHT": "IMAGING",
"MAMMO SCREENING W TOMO BILATERAL": "IMAGING",
"MAMMO SCREENING W TOMO LEFT": "IMAGING",
"MAMMO SCREENING W TOMO RIGHT": "IMAGING",
"MAMMO SCREENING W TOMO W CAD AUGMENTED BILATERAL": "IMAGING",
"MAMMO SCREENING W TOMO W CAD AUGMENTED LEFT": "IMAGING",
"MAMMO SCREENING W TOMO W CAD AUGMENTED RIGHT": "IMAGING",
"MAMMO SCREENING W TOMO W CAD BILATERAL": "IMAGING",
"MAMMO SCREENING W TOMO W CAD LEFT": "IMAGING",
"MAMMO SCREENING W TOMO W CAD RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY 2 LESIONS BILATERAL": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY 2 LESIONS LEFT": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY BILATERAL": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY LEFT": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY LEFT AND RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY SINGLE LESION BILATERAL": "IMAGING",
"MAMMO STEREOTACTIC BIOPSY SINGLE LESION RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BIOSPY BX 1 LESION LEFT AND RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BIOSY 2 LESIONS RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BX 1 LESION LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BX 2 LESIONS LEFT AND 1 LESION RIGHT": "IMAGING",
"MAMMO STEREOTACTIC BX 2 LESIONS LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATIOM 2 LESIONS LEFT AND 1 LESION RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION 1 LESION LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION 1 LESION LEFT AND RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION 2 LESIONS BILATERAL": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION 2 LESIONS LEFT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION 2 LESIONS LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION 2 LESIONS RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION BILATERAL": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION LEFT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION LEFT AND RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION RIGHT": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION SINGLE LESION BILATERAL": "IMAGING",
"MAMMO STEREOTACTIC LOCALIZATION SINGLE LESION LEFT": "IMAGING",
"MAMMO STEREOTATIC LOCALIZATION SINGLE LESION RIGHT": "IMAGING",
"MAMMO SURGICAL SPECIMEN": "IMAGING",
"MAMMO SURGICAL SPECIMEN LEFT": "IMAGING",
"MAMMO SURGICAL SPECIMEN RIGHT": "IMAGING",
"MAMMO UNLISTED": "IMAGING",
"MAMMOGRAM SCREEN UNILATERAL": "IMAGING",
"MAMMOGRAM UNILATERAL DIAGNOSTIC": "IMAGING",
"MAMMOGRAM,SCREEN REDUCED FEE": "IMAGING",
"MAMMOGRAM,UNILATERAL DIAGNOST": "IMAGING",
"MECH REMOV PERICATH OBSTR CV DEV VIA VEN ACCESS": "IMAGING",
"MECKEL'S DIVERT EXAM": "IMAGING",
"METHYLATION MGMT": "PATHOLOGY",
"MOLECULAR": "PATHOLOGY",
"MR ANGIO BRAIN": "IMAGING",
"MR ANGIO IMAGE, HEAD": "IMAGING",
"MR ANGIO NECK": "IMAGING",
"MR ANGIO UPPER EXT RIGHT": "IMAGING",
"MR ANGIO UPPER EXTREMITY BILAT": "IMAGING",
"MR ANGIO UPPER EXTREMITY LEFT": "IMAGING",
"MR ANGIO UPPER EXTREMITY RIGHT": "IMAGING",
"MR CHOLANGIOPANCREATOGRAPHY": "IMAGING",
"MRA ANGIO LOWER EXTREMITY BILAT": "IMAGING",
"MRA ANGIO LOWER EXTREMITY LEFT": "IMAGING",
"MRA ANGIO LOWER EXTREMITY RIGHT": "IMAGING",
"MRA ANGIO SPINE COMBO": "IMAGING",
"MRA HEAD COMBO": "IMAGING",
"MRA HEAD NO CONTRAST": "IMAGING",
"MRA HEAD W/CONTRAST": "IMAGING",
"MRA NECK COMBO": "IMAGING",
"MRA NECK NO CONTRAST": "IMAGING",
"MRA NECK W/CONTRAST": "IMAGING",
"MRCP": "IMAGING",
"MRI BRAIN W CONTRAST": "IMAGING",
"MRI BRAIN W WO CONTRAST": "IMAGING",
"MRI CERVICAL SPINE W WO CONTRAST": "IMAGING",
"MRI CHEST W WO CONTRAST": "IMAGING",
"MRI THORACIC SPINE W WO CONTRAST": "IMAGING",
"MRI ABDOMEN": "IMAGING",
"MRI ABDOMEN AND PELVIS": "IMAGING",
"MRI ABDOMEN AND PELVIS W CONTRAST": "IMAGING",
"MRI ABDOMEN AND PELVIS W WO CONTRAST": "IMAGING",
"MRI ABDOMEN AND PELVIS WO CONTRAST": "IMAGING",
"MRI ABDOMEN COMBO": "IMAGING",
"MRI ABDOMEN CONTRAST": "IMAGING",
"MRI ABDOMEN CYBER KNIFE": "IMAGING",
"MRI ABDOMEN CYBER KNIFE W CONTRAST": "IMAGING",
"MRI ABDOMEN CYBER KNIFE W WO CONTRAST": "IMAGING",
"MRI ABDOMEN CYBER KNIFE WO CONTRAST": "IMAGING",
"MRI ABDOMEN NO CONTRAST": "IMAGING",
"MRI ABDOMEN W CONTRAST": "IMAGING",
"MRI ABDOMEN W WO CONTRAST": "IMAGING",
"MRI ABDOMEN WO CONTRAST": "IMAGING",
"MRI ANGIO LOWER EXTREMITY W CONTRAST BILATERAL": "IMAGING",
"MRI ANGIO LOWER EXTREMITY W CONTRAST LEFT": "IMAGING",
"MRI ANGIO LOWER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"MRI ANGIO LOWER EXTREMITY W WO CONTRAST BILAT": "IMAGING",
"MRI ANGIO LOWER EXTREMITY W WO CONTRAST LEFT": "IMAGING",
"MRI ANGIO LOWER EXTREMITY W WO CONTRAST RT": "IMAGING",
"MRI ANGIO LOWER EXTREMITY WO CONTRAST BILATERAL": "IMAGING",
"MRI ANGIO LOWER EXTREMITY WO CONTRAST LEFT": "IMAGING",
"MRI ANGIO LOWER EXTREMITY WO CONTRAST RIGHT": "IMAGING",
"MRI ANGIOGRAM ABDOMEN": "IMAGING",
"MRI ANGIOGRAM ABDOMEN W CONTRAST": "IMAGING",
"MRI ANGIOGRAM ABDOMEN W RUN-OFF W CONTRAST": "IMAGING",
"MRI ANGIOGRAM ABDOMEN W RUN-OFF W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM ABDOMEN W RUN-OFF WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM ABDOMEN W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM ABDOMEN WITH RUN-OFF": "IMAGING",
"MRI ANGIOGRAM ABDOMEN WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN": "IMAGING",
"MRI ANGIOGRAM BRAIN ARTERIAL": "IMAGING",
"MRI ANGIOGRAM BRAIN ARTERIAL AND VENOUS": "IMAGING",
"MRI ANGIOGRAM BRAIN ARTERIAL W CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN ARTERIAL W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN ARTERIAL WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN VENOUS": "IMAGING",
"MRI ANGIOGRAM BRAIN VENOUS W CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN VENOUS W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN VENOUS WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN W CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM BRAIN WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM CHEST": "IMAGING",
"MRI ANGIOGRAM CHEST W CONTRAST": "IMAGING",
"MRI ANGIOGRAM CHEST W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM CHEST WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM LOWER EXTREMITY": "IMAGING",
"MRI ANGIOGRAM LOWER EXTREMITY BILATERAL": "IMAGING",
"MRI ANGIOGRAM LOWER EXTREMITY LEFT": "IMAGING",
"MRI ANGIOGRAM LOWER EXTREMITY RIGHT": "IMAGING",
"MRI ANGIOGRAM NECK": "IMAGING",
"MRI ANGIOGRAM NECK W CONTRAST": "IMAGING",
"MRI ANGIOGRAM NECK W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM NECK WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM PELVIS": "IMAGING",
"MRI ANGIOGRAM PELVIS W CONTRAST": "IMAGING",
"MRI ANGIOGRAM PELVIS W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM PELVIS WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM SPINE": "IMAGING",
"MRI ANGIOGRAM SPINE W WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM SPINE WO CONTRAST": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY LEFT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY RIGHT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY W CONTRAST LEFT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY W OR WO CONTRAST BILATERAL": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY W WO CONTRAST LEFT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY W WO CONTRAST RIGHT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY WO CONTRAST LEFT": "IMAGING",
"MRI ANGIOGRAM UPPER EXTREMITY WO CONTRAST RIGHT": "IMAGING",
"MRI ANGIOGRAM W CONTRAST": "IMAGING",
"MRI ANKLE JOINT W CONTRAST LEFT": "IMAGING",
"MRI ANKLE JOINT W CONTRAST RIGHT": "IMAGING",
"MRI ANKLE JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI ANKLE JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI ANKLE JOINT WO CONTRAST LEFT": "IMAGING",
"MRI ANKLE JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI ANKLE LEFT": "IMAGING",
"MRI ANKLE NON-JT W CONTRAST LEFT": "IMAGING",
"MRI ANKLE NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI ANKLE NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI ANKLE NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI ANKLE NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI ANKLE NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI ANKLE RIGHT": "IMAGING",
"MRI ARTHROGRAM ANKLE LEFT": "IMAGING",
"MRI ARTHROGRAM ANKLE RIGHT": "IMAGING",
"MRI ARTHROGRAM ELBOW LEFT": "IMAGING",
"MRI ARTHROGRAM ELBOW RIGHT": "IMAGING",
"MRI ARTHROGRAM HIP LEFT": "IMAGING",
"MRI ARTHROGRAM HIP RIGHT": "IMAGING",
"MRI ARTHROGRAM KNEE LEFT": "IMAGING",
"MRI ARTHROGRAM KNEE RIGHT": "IMAGING",
"MRI ARTHROGRAM SHOULDER LEFT": "IMAGING",
"MRI ARTHROGRAM SHOULDER RIGHT": "IMAGING",
"MRI ARTHROGRAM WRIST LEFT": "IMAGING",
"MRI ARTHROGRAM WRIST RIGHT": "IMAGING",
"MRI BONE MARROW BLOOD SUPPLY": "IMAGING",
"MRI BRACHIAL PLEXUS BILATERAL": "IMAGING",
"MRI BRACHIAL PLEXUS LT": "IMAGING",
"MRI BRACHIAL PLEXUS RT": "IMAGING",
"MRI BRAIN": "IMAGING",
"MRI BRAIN 3T WITH DTI AND PERFUSION": "IMAGING",
"MRI BRAIN 3T WITH DTI AND PERFUSION W CONTRAST": "IMAGING",
"MRI BRAIN 3T WITH DTI AND PERFUSION W WO CONTRAST": "IMAGING",
"MRI BRAIN 3T WITH DTI AND PERFUSION WO CONTRAST": "IMAGING",
"MRI BRAIN 3T WITH PERFUSION": "IMAGING",
"MRI BRAIN 3T WITH PERFUSION W CONTRAST": "IMAGING",
"MRI BRAIN 3T WITH PERFUSION W WO CONTRAST": "IMAGING",
"MRI BRAIN 3T WITH PERFUSION WO CONTRAST": "IMAGING",
"MRI BRAIN BY PHYSICIAN OR PSYCHOLOGIST ADMIN NEURO TEST ": "IMAGING",
"MRI BRAIN COMBO": "IMAGING",
"MRI BRAIN CYBER KNIFE": "IMAGING",
"MRI BRAIN CYBER KNIFE W CONTRAST": "IMAGING",
"MRI BRAIN CYBER KNIFE W WO CONTRAST": "IMAGING",
"MRI BRAIN CYBER KNIFE WO CONTRAST": "IMAGING",
"MRI BRAIN DTI ONLY WO CONTRAST": "IMAGING",
"MRI BRAIN FUNCTIONAL IMAGING": "IMAGING",
"MRI BRAIN LEVEL 1": "IMAGING",
"MRI BRAIN LEVEL 1 W CONTRAST": "IMAGING",
"MRI BRAIN LEVEL 1 W WO CONTRAST": "IMAGING",
"MRI BRAIN LEVEL 1 WO CONTRAST": "IMAGING",
"MRI BRAIN NO CONTRAST": "IMAGING",
"MRI BRAIN SPECTROSCOPY": "IMAGING",
"MRI BRAIN STEALTH": "IMAGING",
"MRI BRAIN STEALTH W CONTRAST": "IMAGING",
"MRI BRAIN STEALTH WO CONTRAST": "IMAGING",
"MRI BRAIN W/CONTRAST": "IMAGING",
"MRI BRAIN W/DYE": "IMAGING",
"MRI BRAIN W/O & W/DYE": "IMAGING",
"MRI BRAIN W/O DYE": "IMAGING",
"MRI BRAIN WITH DTI": "IMAGING",
"MRI BRAIN WITH DTI W CONTRAST": "IMAGING",
"MRI BRAIN WITH DTI W WO CONTRAST": "IMAGING",
"MRI BRAIN WITH DTI WO CONTRAST": "IMAGING",
"MRI BRAIN WITH IAC W CONTRAST": "IMAGING",
"MRI BRAIN WITH IAC W WO CONTRAST": "IMAGING",
"MRI BRAIN WITH IAC WO CONTRAST": "IMAGING",
"MRI BRAIN WITH PITUITARY W CONTRAST": "IMAGING",
"MRI BRAIN WITH PITUITARY W WO CONTRAST": "IMAGING",
"MRI BRAIN WITH PITUITARY WO CONTRAST": "IMAGING",
"MRI BRAIN WO CONTRAST": "IMAGING",
"MRI BREAST BILATERAL": "IMAGING",
"MRI BREAST LEFT": "IMAGING",
"MRI BREAST RIGHT": "IMAGING",
"MRI BREAST W CAD BILATERAL": "IMAGING",
"MRI BREAST W CAD LEFT": "IMAGING",
"MRI BREAST W CAD RIGHT": "IMAGING",
"MRI BREAST W/WO CONTR UNILATERAL": "IMAGING",
"MRI BREAST W/WO CONTRAST BILATERAL": "IMAGING",
"MRI BREAST WITH AND OR WO CONTRAST BILAT": "IMAGING",
"MRI BREAST WITH AND OR WO CONTRAST UNILAT": "IMAGING",
"MRI BREAST WO CAD BILATERAL": "IMAGING",
"MRI BREAST WO CAD LEFT": "IMAGING",
"MRI BREAST WO CAD RIGHT": "IMAGING",
"MRI BREASTS BILATERAL": "IMAGING",
"MRI CARDIAC FUNCTION": "IMAGING",
"MRI CARDIAC IMAGING": "IMAGING",
"MRI CARDIAC LIMITED FUNC STUDYY": "IMAGING",
"MRI CARDIAC VEL FLOW MAPPING": "IMAGING",
"MRI CARDIAC W CONTRAST": "IMAGING",
"MRI CARDIAC W CONTRAST W STRESS": "IMAGING",
"MRI CARDIAC WO CONTRAST": "IMAGING",
"MRI CARDIAC WO CONTRAST W STRESS": "IMAGING",
"MRI CEREBROVASCUALR": "IMAGING",
"MRI CERVICAL SPINE": "IMAGING",
"MRI CERVICAL SPINE COMBO": "IMAGING",
"MRI CERVICAL SPINE NO CONTRAST": "IMAGING",
"MRI CERVICAL SPINE W CONTRAST": "IMAGING",
"MRI CERVICAL SPINE W/CONTRAST": "IMAGING",
"MRI CERVICAL SPINE WO CONTRAST": "IMAGING",
"MRI CHEST": "IMAGING",
"MRI CHEST COMBO": "IMAGING",
"MRI CHEST CYBER KNIFE": "IMAGING",
"MRI CHEST CYBER KNIFE W CONTRAST": "IMAGING",
"MRI CHEST CYBER KNIFE W WO CONTRAST": "IMAGING",
"MRI CHEST CYBER KNIFE WO CONTRAST": "IMAGING",
"MRI CHEST NO CONTRAST": "IMAGING",
"MRI CHEST W CONTRAST": "IMAGING",
"MRI CHEST W/CONTRAST": "IMAGING",
"MRI CHEST WO CONTRAST": "IMAGING",
"MRI CHOLANGIOPANCREATOGRAPHY": "IMAGING",
"MRI ELBOW JOINT W CONTRAST LEFT": "IMAGING",
"MRI ELBOW JOINT W CONTRAST RIGHT": "IMAGING",
"MRI ELBOW JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI ELBOW JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI ELBOW JOINT WO CONTRAST LEFT": "IMAGING",
"MRI ELBOW JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI ELBOW LEFT": "IMAGING",
"MRI ELBOW NON-JT W CONTRAST LEFT": "IMAGING",
"MRI ELBOW NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI ELBOW NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI ELBOW NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI ELBOW NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI ELBOW NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI ELBOW RIGHT": "IMAGING",
"MRI ENTEROGRAPHY": "IMAGING",
"MRI ENTEROGRAPHY ABD PELVIS W CONTRAST": "IMAGING",
"MRI ENTEROGRAPHY ABD PELVIS W WO CONTRAST": "IMAGING",
"MRI ENTEROGRAPY ABD PELVIS WO CONTRAST": "IMAGING",
"MRI FACE": "IMAGING",
"MRI FACE COMBO": "IMAGING",
"MRI FACE CONTRAST": "IMAGING",
"MRI FACE NO CONTRAST": "IMAGING",
"MRI FACE W CONTRAST": "IMAGING",
"MRI FACE W WO CONTRAST": "IMAGING",
"MRI FACE WO CONTRAST": "IMAGING",
"MRI FACE/NECK COMBO": "IMAGING",
"MRI FEMUR LEFT": "IMAGING",
"MRI FEMUR RIGHT": "IMAGING",
"MRI FEMUR W CONTRAST LEFT": "IMAGING",
"MRI FEMUR W CONTRAST RIGHT": "IMAGING",
"MRI FEMUR W WO CONTRAST LEFT": "IMAGING",
"MRI FEMUR W WO CONTRAST RIGHT": "IMAGING",
"MRI FEMUR WO CONTRAST LEFT": "IMAGING",
"MRI FEMUR WO CONTRAST RIGHT": "IMAGING",
"MRI FINGER THUMB LEFT": "IMAGING",
"MRI FINGER THUMB RIGHT": "IMAGING",
"MRI FINGER THUMB W CONTRAST LEFT": "IMAGING",
"MRI FINGER THUMB W CONTRAST RIGHT": "IMAGING",
"MRI FINGER THUMB W WO CONTRAST LEFT": "IMAGING",
"MRI FINGER THUMB W WO CONTRAST RIGHT": "IMAGING",
"MRI FINGER THUMB WO CONTRAST LEFT": "IMAGING",
"MRI FINGER THUMB WO CONTRAST RIGHT": "IMAGING",
"MRI FOOT JOINT W CONTRAST LEFT": "IMAGING",
"MRI FOOT JOINT W CONTRAST RIGHT": "IMAGING",
"MRI FOOT JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI FOOT JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI FOOT JOINT WO CONTRAST LEFT": "IMAGING",
"MRI FOOT JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI FOOT LEFT": "IMAGING",
"MRI FOOT NON-JT W CONTRAST LEFT": "IMAGING",
"MRI FOOT NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI FOOT NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI FOOT NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI FOOT NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI FOOT NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI FOOT RIGHT": "IMAGING",
"MRI FOR TISSUE ABLATION": "IMAGING",
"MRI FOREARM LEFT": "IMAGING",
"MRI FOREARM RIGHT": "IMAGING",
"MRI FOREARM W CONTRAST LEFT": "IMAGING",
"MRI FOREARM W CONTRAST RIGHT": "IMAGING",
"MRI FOREARM W WO CONTRAST LEFT": "IMAGING",
"MRI FOREARM W WO CONTRAST RIGHT": "IMAGING",
"MRI FOREARM WO CONTRAST LEFT": "IMAGING",
"MRI FOREARM WO CONTRAST RIGHT": "IMAGING",
"MRI GUIDANCE FOR NEEDLE PLACE": "IMAGING",
"MRI GUIDE BREAST BIOPSY 2 LESIONS BILATERAL": "IMAGING",
"MRI GUIDE BREAST BIOPSY 2 LESIONS LEFT": "IMAGING",
"MRI GUIDE BREAST BIOPSY 2 LESIONS RIGHT": "IMAGING",
"MRI GUIDE BREAST BIOPSY SINGLE LESION BILATERAL": "IMAGING",
"MRI GUIDE BREAST BIOPSY SINGLE LESION LEFT": "IMAGING",
"MRI GUIDE BREAST BIOPSY SINGLE LESION RIGHT": "IMAGING",
"MRI GUIDE BREAST BIOPSY/LOCALIATION LEFT": "IMAGING",
"MRI GUIDE BREAST BIOPSY/LOCALIZATION": "IMAGING",
"MRI GUIDE BREAST BIOPSY/LOCALIZATION BILATERAL": "IMAGING",
"MRI GUIDE BREAST BIOPSY/LOCALIZATION LEFT AND RIGHT": "IMAGING",
"MRI GUIDE BREAST BIOSY/LOCALIZATION RIGHT": "IMAGING",
"MRI GUIDE BREAST BX 1 LESION LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MRI GUIDE BREAST BX 1 LESION LEFT AND RIGHT": "IMAGING",
"MRI GUIDE BREAST BX 2 LESION LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MRI GUIDE BREAST BX 2 LESIONS LEFT AND 1 LESION RIGHT": "IMAGING",
"MRI GUIDE BREAST PLACE LOC DEVICE 1 LESION LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MRI GUIDE BREAST PLACE LOC DEVICE 1 LESION LEFT AND RIGHT": "IMAGING",
"MRI GUIDE BREAST PLACE LOC DEVICE 2 LESIONS LEFT AND 2 LESIONS RIGHT": "IMAGING",
"MRI GUIDE BREAST PLACE LOC DEVISE 2 LESIONS LEFT AND 1 LESION RIGHT": "IMAGING",
"MRI GUIDE BREAST PLACEMENT LOC DEVICE 2 LESIONS BILATERAL": "IMAGING",
"MRI GUIDE BREAST PLACEMENT LOC DEVICE 2 LESIONS LEFT": "IMAGING",
"MRI GUIDE BREAST PLACEMENT LOC DEVICE 2 LESIONS RIGHT": "IMAGING",
"MRI GUIDE BREAST PLACEMENT LOC DEVICE SINGLE LESION BILATERAL": "IMAGING",
"MRI GUIDE BREAST PLACEMENT LOC DEVICE SINGLE LESION LEFT": "IMAGING",
"MRI GUIDE BREAST PLACEMENT LOC DEVICE SINGLE LESION RIGHT": "IMAGING",
"MRI GUIDE NEEDLE FOR BX, ASP, INJ": "IMAGING",
"MRI GUIDE NEEDLE PLACE FOR BX/ASP/LOC": "IMAGING",
"MRI GUIDED NEEDLE PLACMENT BREAST BIOPSY": "IMAGING",
"MRI HAND JOINT W CONTRAST LEFT": "IMAGING",
"MRI HAND JOINT W CONTRAST RIGHT": "IMAGING",
"MRI HAND JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI HAND JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI HAND JOINT WO CONTRAST LEFT": "IMAGING",
"MRI HAND JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI HAND LEFT": "IMAGING",
"MRI HAND NON-JT W CONTRAST LEFT": "IMAGING",
"MRI HAND NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI HAND NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI HAND NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI HAND NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI HAND NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI HAND RIGHT": "IMAGING",
"MRI HEAD GAMMA KNIFE": "IMAGING",
"MRI HEAD GAMMA KNIFE W CONTRAST": "IMAGING",
"MRI HEAD GAMMA KNIFE W WO CONTRAST": "IMAGING",
"MRI HEAD GAMMA KNIFE WO CONTRAST": "IMAGING",
"MRI HIP ARTHROGRAM LEFT": "IMAGING",
"MRI HIP ARTHROGRAM RIGHT": "IMAGING",
"MRI HIP JOINT W CONTRAST LEFT": "IMAGING",
"MRI HIP JOINT W CONTRAST RIGHT": "IMAGING",
"MRI HIP JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI HIP JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI HIP JOINT WO CONTRAST LEFT": "IMAGING",
"MRI HIP JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI HIP LEFT": "IMAGING",
"MRI HIP NON-JT W CONTRAST LEFT": "IMAGING",
"MRI HIP NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI HIP NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI HIP NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI HIP NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI HIP NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI HIP RIGHT": "IMAGING",
"MRI HUMERUS LEFT": "IMAGING",
"MRI HUMERUS RIGHT": "IMAGING",
"MRI HUMERUS W CONTRAST LEFT": "IMAGING",
"MRI HUMERUS W CONTRAST RIGHT": "IMAGING",
"MRI HUMERUS W WO CONTRAST LEFT": "IMAGING",
"MRI HUMERUS W WO CONTRAST RIGHT": "IMAGING",
"MRI HUMERUS WO CONTRAST LEFT": "IMAGING",
"MRI HUMERUS WO CONTRAST RIGHT": "IMAGING",
"MRI KNEE ARTHROGRAM LT": "IMAGING",
"MRI KNEE ARTHROGRAM RT": "IMAGING",
"MRI KNEE JOINT W CONTRAST LEFT": "IMAGING",
"MRI KNEE JOINT W CONTRAST RIGHT": "IMAGING",
"MRI KNEE JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI KNEE JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI KNEE JOINT WO CONTRAST LEFT": "IMAGING",
"MRI KNEE JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI KNEE LEFT": "IMAGING",
"MRI KNEE NON-JT W CONTRAST LEFT": "IMAGING",
"MRI KNEE NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI KNEE NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI KNEE NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI KNEE NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI KNEE NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI KNEE RIGHT": "IMAGING",
"MRI LIVER": "IMAGING",
"MRI LIVER COMBO": "IMAGING",
"MRI LIVER NO CONTRAST": "IMAGING",
"MRI LIVER W/CONTRAST": "IMAGING",
"MRI LOW EXT JOINT COMBO BILAT": "IMAGING",
"MRI LOW EXT JOINT COMBO LEFT": "IMAGING",
"MRI LOW EXT JOINT COMBO RIGHT": "IMAGING",
"MRI LOW EXT JOINT CONT BILAT": "IMAGING",
"MRI LOW EXT JOINT CONT LEFT": "IMAGING",
"MRI LOW EXT JOINT CONT RIGHT": "IMAGING",
"MRI LOW EXT JOINT NO CONT BIL": "IMAGING",
"MRI LOW EXT JOINT NO CONT LFT": "IMAGING",
"MRI LOW EXT JOINT NO CONT RT": "IMAGING",
"MRI LOW EXT(NON-JT)COMBO BILAT": "IMAGING",
"MRI LOW EXT/NON-JT/COMBO LFT": "IMAGING",
"MRI LOW EXT/NON-JT/COMBO RT": "IMAGING",
"MRI LOW EXT/NON-JT/CONT BILAT": "IMAGING",
"MRI LOW EXT/NON-JT/CONT LEFT": "IMAGING",
"MRI LOW EXT/NON-JT/CONT RT": "IMAGING",
"MRI LOW EXT/NON-JT/NO CONT BIL": "IMAGING",
"MRI LOW EXT/NON-JT/NO CONT LFT": "IMAGING",
"MRI LOW EXT/NON-JT/NO CONT RT": "IMAGING",
"MRI LOWER EXT COMBO": "IMAGING",
"MRI LOWER EXT JT COMBO": "IMAGING",
"MRI LOWER EXT JT W/CONTRAST": "IMAGING",
"MRI LOWER EXT JT W/O CONTRAST": "IMAGING",
"MRI LOWER EXT W/CONTRAST": "IMAGING",
"MRI LOWER EXT W/O CONTRAST": "IMAGING",
"MRI LOWER EXTREM JOINT W CONTRAST": "IMAGING",
"MRI LOWER EXTREM JOINT W CONTRAST LEFT": "IMAGING",
"MRI LOWER EXTREM JOINT W CONTRAST RIGHT": "IMAGING",
"MRI LOWER EXTREM JOINT W WO CONTRAST": "IMAGING",
"MRI LOWER EXTREM JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI LOWER EXTREM JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI LOWER EXTREM JOINT WO CONTRAST": "IMAGING",
"MRI LOWER EXTREM JOINT WO CONTRAST LEFT": "IMAGING",
"MRI LOWER EXTREM JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI LOWER EXTREMITY BILAT": "IMAGING",
"MRI LOWER EXTREMITY LEFT": "IMAGING",
"MRI LOWER EXTREMITY LT": "IMAGING",
"MRI LOWER EXTREMITY RIGHT": "IMAGING",
"MRI LOWER EXTREMITY RT": "IMAGING",
"MRI LOWER EXTREMITY W CONTRAST": "IMAGING",
"MRI LOWER EXTREMITY W CONTRAST LEFT": "IMAGING",
"MRI LOWER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"MRI LOWER EXTREMITY W WO CONTRAST": "IMAGING",
"MRI LOWER EXTREMITY W WO CONTRAST LEFT": "IMAGING",
"MRI LOWER EXTREMITY W WO CONTRAST RIGHT": "IMAGING",
"MRI LOWER EXTREMITY WO CONTRAST": "IMAGING",
"MRI LOWER EXTREMITY WO CONTRAST LEFT": "IMAGING",
"MRI LOWER EXTREMITY WO CONTRAST RIGHT": "IMAGING",
"MRI LUMBAR SPINE": "IMAGING",
"MRI LUMBAR SPINE COMBO": "IMAGING",
"MRI LUMBAR SPINE NO CONTRAST": "IMAGING",
"MRI LUMBAR SPINE W CONTRAST": "IMAGING",
"MRI LUMBAR SPINE W WO CONTRAST": "IMAGING",
"MRI LUMBAR SPINE W/CONTRAST": "IMAGING",
"MRI LUMBAR SPINE WO CONTRAST": "IMAGING",
"MRI LUMBOSACRAL PLEXUS": "IMAGING",
"MRI LUMBOSACRAL PLEXUS W WO CONTRAST": "IMAGING",
"MRI LUMBOSACRAL PLEXUS WO CONTRAST": "IMAGING",
"MRI MAMM W/WO CONTRAST BILATERAL": "IMAGING",
"MRI MAMM W/WO CONTRAST UNILATERAL": "IMAGING",
"MRI MRCP": "IMAGING",
"MRI MYOCARDIUM": "IMAGING",
"MRI MYOCARDIUM CONTRAST": "IMAGING",
"MRI MYOCARDIUM NO CONTRAST": "IMAGING",
"MRI NECK": "IMAGING",
"MRI NECK COMBO": "IMAGING",
"MRI NECK CONTRAST": "IMAGING",
"MRI NECK NO CONTRAST": "IMAGING",
"MRI NECK W CONTRAST": "IMAGING",
"MRI NECK W WO CONTRAST": "IMAGING",
"MRI NECK WO CONTRAST": "IMAGING",
"MRI ORBITS": "IMAGING",
"MRI ORBITS COMBO": "IMAGING",
"MRI ORBITS CONTRAST": "IMAGING",
"MRI ORBITS NO CONTRAST": "IMAGING",
"MRI ORBITS W CONTRAST": "IMAGING",
"MRI ORBITS W WO CONTRAST": "IMAGING",
"MRI ORBITS WO CONTRAST": "IMAGING",
"MRI PELVIS": "IMAGING",
"MRI PELVIS CYBER KNIFE": "IMAGING",
"MRI PELVIS CYBER KNIFE W CONTRAST": "IMAGING",
"MRI PELVIS CYBER KNIFE W WO CONTRAST": "IMAGING",
"MRI PELVIS CYBER KNIFE WO CONTRAST": "IMAGING",
"MRI PELVIS W CONTRAST": "IMAGING",
"MRI PELVIS W WO CONTRAST": "IMAGING",
"MRI PELVIS WO CONTRAST": "IMAGING",
"MRI PITUITARY": "IMAGING",
"MRI PITUITARY W CONTRAST": "IMAGING",
"MRI PITUITARY W WO CONTRAST": "IMAGING",
"MRI PITUITARY WO CONTRAST": "IMAGING",
"MRI PROC UNLISTED": "IMAGING",
"MRI PROSTATE 3T": "IMAGING",
"MRI PROSTATE 3T W CONTRAST": "IMAGING",
"MRI PROSTATE 3T W WO CONTRAST": "IMAGING",
"MRI PROSTATE 3T WO CONTRAST": "IMAGING",
"MRI QUICK BRAIN": "IMAGING",
"MRI QUICK BRAIN W CONTRAST": "IMAGING",
"MRI QUICK BRAIN W WO CONTRAST": "IMAGING",
"MRI QUICK BRAIN WO CONTRAST": "IMAGING",
"MRI QUICK CERVICAL SPINE W CONTRAST": "IMAGING",
"MRI QUICK CERVICAL SPINE W WO CONTRAST": "IMAGING",
"MRI QUICK CERVICAL SPINE WO CONTRAST": "IMAGING",
"MRI QUICK LUMBAR SPINE W CONTRAST": "IMAGING",
"MRI QUICK LUMBAR SPINE W WO CONTRAST": "IMAGING",
"MRI QUICK LUMBAR SPINE WO CONTRAST": "IMAGING",
"MRI QUICK SPINE CERVICAL": "IMAGING",
"MRI QUICK SPINE LUMBAR": "IMAGING",
"MRI QUICK SPINE THORACIC": "IMAGING",
"MRI QUICK THORACIC SPINE W CONTRAST": "IMAGING",
"MRI QUICK THORACIC SPINE W WO CONTRAST": "IMAGING",
"MRI QUICK THORACIC SPINE WO CONTRAST": "IMAGING",
"MRI RAD REVIEW 2ND OPINION": "IMAGING",
"MRI RADIOLOGIST REVIEW OF OUTSIDE IMAGES": "IMAGING",
"MRI RECTUM 3T": "IMAGING",
"MRI RECTUM 3T W CONTRAST": "IMAGING",
"MRI RECTUM 3T W WO CONTRAST": "IMAGING",
"MRI RECTUM 3T WO CONTRAST": "IMAGING",
"MRI SHOULDER ARTHRO LFT": "IMAGING",
"MRI SHOULDER ARTHRO RT": "IMAGING",
"MRI SHOULDER ARTHROGRAM LT": "IMAGING",
"MRI SHOULDER ARTHROGRAM RT": "IMAGING",
"MRI SHOULDER JOINT W CONTRAST LEFT": "IMAGING",
"MRI SHOULDER JOINT W CONTRAST RIGHT": "IMAGING",
"MRI SHOULDER JOINT W WO CONTRAST LEFT]": "IMAGING",
"MRI SHOULDER JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI SHOULDER JOINT WO CONTRAST LEFT": "IMAGING",
"MRI SHOULDER JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI SHOULDER LEFT": "IMAGING",
"MRI SHOULDER NON-JT W CONTRAST LEFT": "IMAGING",
"MRI SHOULDER NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI SHOULDER NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI SHOULDER NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI SHOULDER NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI SHOULDER NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI SHOULDER RIGHT": "IMAGING",
"MRI SPECTROSCOPY": "IMAGING",
"MRI SPINE CYBER KNIFE": "IMAGING",
"MRI SPINE CYBER KNIFE CERVICAL W CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE CERVICAL W WO CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE CERVICAL WO CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE LUMBAR W CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE LUMBAR W WO CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE LUMBAR WO CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE THORACIC W CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE THORACIC W WO CONTRAST": "IMAGING",
"MRI SPINE CYBER KNIFE THORACIC WO CONTRAST": "IMAGING",
"MRI TEMPORAL MANDIBULAR JT": "IMAGING",
"MRI THORACIC SPINE": "IMAGING",
"MRI THORACIC SPINE COMBO": "IMAGING",
"MRI THORACIC SPINE NO CONTRAST": "IMAGING",
"MRI THORACIC SPINE W CONTRAST": "IMAGING",
"MRI THORACIC SPINE W/CONTRAST": "IMAGING",
"MRI THORACIC SPINE WO CONTRAST": "IMAGING",
"MRI TIBIA-FIBULA LEFT": "IMAGING",
"MRI TIBIA-FIBULA RIGHT": "IMAGING",
"MRI TIBIA-FIBULA W CONTRAST LEFT": "IMAGING",
"MRI TIBIA-FIBULA W CONTRAST RIGHT": "IMAGING",
"MRI TIBIA-FIBULA W WO CONTRAST LEFT": "IMAGING",
"MRI TIBIA-FIBULA W WO CONTRAST RIGHT": "IMAGING",
"MRI TIBIA-FIBULA WO CONTRAST LEFT": "IMAGING",
"MRI TIBIA-FIBULA WO CONTRAST RIGHT": "IMAGING",
"MRI TOE LEFT": "IMAGING",
"MRI TOE RIGHT": "IMAGING",
"MRI TOE W CONTRAST LEFT": "IMAGING",
"MRI TOE W CONTRAST RIGHT": "IMAGING",
"MRI TOE W WO CONTRAST LEFT": "IMAGING",
"MRI TOE W WO CONTRAST RIGHT": "IMAGING",
"MRI TOE WO CONTRAST LEFT": "IMAGING",
"MRI TOE WO CONTRAST RIGHT": "IMAGING",
"MRI UNLISTED": "IMAGING",
"MRI UP EXT (NON-JT)COMBO BILAT": "IMAGING",
"MRI UP EXT (NON-JT)COMBO LEFT": "IMAGING",
"MRI UP EXT (NON-JT)COMBO RT": "IMAGING",
"MRI UP EXT (NON-JT)CONT RIGHT": "IMAGING",
"MRI UP EXT(JOINT) COMBO BILAT": "IMAGING",
"MRI UP EXT(JOINT) COMBO LEFT": "IMAGING",
"MRI UP EXT(JOINT)COMBO RIGHT": "IMAGING",
"MRI UP EXT(JOINT)CONT BILAT": "IMAGING",
"MRI UP EXT(JOINT)CONT LEFT": "IMAGING",
"MRI UP EXT(JOINT)CONT RIGHT": "IMAGING",
"MRI UP EXT(JOINT)NO CONT BILAT": "IMAGING",
"MRI UP EXT(JOINT)NO CONT LEFT": "IMAGING",
"MRI UP EXT(JOINT)NO CONT RT": "IMAGING",
"MRI UP EXT(NON-JT)CONT LEFT": "IMAGING",
"MRI UP EXT(NON-JT)CONTR BILAT": "IMAGING",
"MRI UP EXT(NON-JT)NO CONT BILA": "IMAGING",
"MRI UP EXT(NON-JT)NO CONT LFT": "IMAGING",
"MRI UP EXT(NON-JT)NO CONT RT": "IMAGING",
"MRI UPPER EXT COMBO": "IMAGING",
"MRI UPPER EXT JT COMBO": "IMAGING",
"MRI UPPER EXT JT W/CONTRAST": "IMAGING",
"MRI UPPER EXT JT W/O CONTRAST": "IMAGING",
"MRI UPPER EXT W/CONTRAST": "IMAGING",
"MRI UPPER EXT W/O CONTRAST": "IMAGING",
"MRI UPPER EXTREM JOINT W CONTRAST LEFT": "IMAGING",
"MRI UPPER EXTREM JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI UPPER EXTREM JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI UPPER EXTREM JOINT WO CONTRAST LEFT": "IMAGING",
"MRI UPPER EXTREMITY BILAT": "IMAGING",
"MRI UPPER EXTREMITY JOINT W CONTRAST": "IMAGING",
"MRI UPPER EXTREMITY JOINT W WO CONTRAST": "IMAGING",
"MRI UPPER EXTREMITY JOINT WO CONTRAST": "IMAGING",
"MRI UPPER EXTREMITY LEFT": "IMAGING",
"MRI UPPER EXTREMITY LT": "IMAGING",
"MRI UPPER EXTREMITY RIGHT": "IMAGING",
"MRI UPPER EXTREMITY RT": "IMAGING",
"MRI UPPER EXTREMITY W CONTRAST": "IMAGING",
"MRI UPPER EXTREMITY W CONTRAST LEFT": "IMAGING",
"MRI UPPER EXTREMITY W CONTRAST RIGHT": "IMAGING",
"MRI UPPER EXTREMITY W WO CONTRAST": "IMAGING",
"MRI UPPER EXTREMITY W WO CONTRAST LEFT": "IMAGING",
"MRI UPPER EXTREMITY W WO CONTRAST RIGHT": "IMAGING",
"MRI UPPER EXTREMITY WO CONTRAST": "IMAGING",
"MRI UPPER EXTREMITY WO CONTRAST LEFT": "IMAGING",
"MRI WHOLE BODY": "IMAGING",
"MRI WHOLE BODY LI FRAUMENI SYNDROME": "IMAGING",
"MRI WRIST JOINT W CONTRAST LEFT": "IMAGING",
"MRI WRIST JOINT W CONTRAST RIGHT": "IMAGING",
"MRI WRIST JOINT W WO CONTRAST LEFT": "IMAGING",
"MRI WRIST JOINT W WO CONTRAST RIGHT": "IMAGING",
"MRI WRIST JOINT WO CONTRAST LEFT": "IMAGING",
"MRI WRIST JOINT WO CONTRAST RIGHT": "IMAGING",
"MRI WRIST LEFT": "IMAGING",
"MRI WRIST NON-JT W CONTRAST LEFT": "IMAGING",
"MRI WRIST NON-JT W CONTRAST RIGHT": "IMAGING",
"MRI WRIST NON-JT W WO CONTRAST LEFT": "IMAGING",
"MRI WRIST NON-JT W WO CONTRAST RIGHT": "IMAGING",
"MRI WRIST NON-JT WO CONTRAST LEFT": "IMAGING",
"MRI WRIST NON-JT WO CONTRAST RIGHT": "IMAGING",
"MRI WRIST RIGHT": "IMAGING",
"MRI, BONE MARROW": "IMAGING",
"MRI, BREAST UNILAT": "IMAGING",
"MRI, FACE, NECK": "IMAGING",
"MRI-ORBIT/FACE/NECK W/CONTRAST": "IMAGING",
"MUSCULOSKELETAL NUCLEAR EXAM": "IMAGING",
"MYCARD PERF PLANAR W WALL MOTION SINGLE STUDY": "IMAGING",
"MYELOGRAPHY POST FOSSA": "IMAGING",
"MYOCARD PERF PLANAR W WALL MOTION MULTIPLE STUDIES": "IMAGING",
"MYOCARDIAL IMAGE MULTIPLE,PLANAR": "IMAGING",
"MYOCARDIAL IMAGE SINGLE,PLANAR": "IMAGING",
"MYOCARDIAL IMAGE SINGLE,SPECT": "IMAGING",
"MYOCARDIAL PERFUSION REST OR STRESS MULT ST": "IMAGING",
"MYOCARDIAL PERFUSION REST OR STRESS SINGLE": "IMAGING",
"MYOCARDIAL STRAIN IMAGING QUANTITATIVE ASSESSMENT OF MYOCARDIAL MECH": "IMAGING",
"MYOCARDIAL SYMPATH INNERVATION IMAG PLANAR W/TOMOG SPECT": "IMAGING",
"MYOCARDIAL SYMPATHETIC INNERVATION IMAGING PLANAR QUAALI": "IMAGING",
"MYOCARDL PERF REST STRESS": "IMAGING",
"NEEDLE CORE BX BREAST LESION": "IMAGING",
"NEEDLE CORE BX BREAST LESION, OTHER BREAST": "IMAGING",
"NEEDLE CORE BX BRST LES,OTH BRST": "IMAGING",
"NEEDLE LOCALIZATION FLUORO BY RAD": "IMAGING",
"NEEDLE LOCALIZATION FLUORO/RAD": "IMAGING",
"NERV SYS NUCL EXAM UNLISTED": "IMAGING",
"NERVE CONDUCTION STUDY": "IMAGING",
"NERVE CONDUCTION STUDY W/O F WAVE": "IMAGING",
"NM ABSCESS LOC LTD": "IMAGING",
"NM ABSCESS LOC LTD W SPECT": "IMAGING",
"NM ABSCESS LOC LTD W SPECT + ADDL SPECT": "IMAGING",
"NM ABSCESS LOC SPECT": "IMAGING",
"NM ABSCESS LOC WHOLE BODY": "IMAGING",
"NM ABSCESS LOC WHOLE BODY W SPECT": "IMAGING",
"NM ABSCESS LOC WHOLE BODY W SPECT + ADDL SPECT": "IMAGING",
"NM ABSCESS LOCALIZATION CERETEC": "IMAGING",
"NM ABSCESS LOCALIZATION GALLIUM": "IMAGING",
"NM ABSCESS LOCALIZATION INDIUM": "IMAGING",
"NM ABSCESS LOCALIZATION LIMITED": "IMAGING",
"NM ABSCESS LOCALIZATION SPECT": "IMAGING",
"NM ABSCESS LOCALIZATION WHOLE BODY": "IMAGING",
"NM ADRENAL SCAN": "IMAGING",
"NM AMYLOID CARDIAC IMAGING": "IMAGING",
"NM BEXXAR TX ADMIN": "IMAGING",
"NM BEXXAR TX PLANNING": "IMAGING",
"NM BONE MARROW IMAGING": "IMAGING",
"NM BONE MARROW IMAGING AND WBC": "IMAGING",
"NM BONE MARROW IMAGING LTD": "IMAGING",
"NM BONE MARROW IMAGING LTD W SPECT": "IMAGING",
"NM BONE MARROW IMAGING MULTI": "IMAGING",
"NM BONE MARROW IMAGING MULTI W SPECT": "IMAGING",
"NM BONE MARROW IMAGING WHOLE BODY": "IMAGING",
"NM BONE MARROW IMAGING WHOLE BODY W SPECT": "IMAGING",
"NM BONE MARROW LTD AND WBC LTD": "IMAGING",
"NM BONE MARROW LTD W SPECT AND WBC LTD W SPECT": "IMAGING",
"NM BONE MARROW MULTI AND WBC MULTI": "IMAGING",
"NM BONE MARROW MULTI W SPECT AND WBC MULTI W SPECT": "IMAGING",
"NM BONE MARROW WB W SPECT AND WBC WB W SPECT": "IMAGING",
"NM BONE MARROW WHOLE BODY AND WBC WHOLE BODY": "IMAGING",
"NM BONE SCAN": "IMAGING",
"NM BONE SCAN 3 PHASE": "IMAGING",
"NM BONE SCAN 3 PHASE W SPECT+SPECT": "IMAGING",
"NM BONE SCAN 3 PHASE WITH SPECT": "IMAGING",
"NM BONE SCAN LIMITED": "IMAGING",
"NM BONE SCAN LIMITED W SPECT+SPECT": "IMAGING",
"NM BONE SCAN LIMITED WITH SPECT": "IMAGING",
"NM BONE SCAN MULTIPLE": "IMAGING",
"NM BONE SCAN MULTIPLE WITH SPECT": "IMAGING",
"NM BONE SCAN SPECT": "IMAGING",
"NM BONE SCAN SPECT WITH SPECT": "IMAGING",
"NM BONE SCAN TOMOGRAM": "IMAGING",
"NM BONE SCAN WHOLE BODY": "IMAGING",
"NM BONE SCAN WHOLE BODY W SPECT+SPECT": "IMAGING",
"NM BONE SCAN WHOLE BODY WITH SPECT": "IMAGING",
"NM BRAIN LIMITED W VASCULAR FLOW": "IMAGING",
"NM BRAIN SCAN COMPLETE W VASCULAR FLOW": "IMAGING",
"NM BRAIN SCAN PLANAR": "IMAGING",
"NM BRAIN SPECT": "IMAGING",
"NM BRAIN SPECT DATSCAN": "IMAGING",
"NM BRAIN VASCULAR FLOW ONLY": "IMAGING",
"NM CARDIAC BLOOD POOL IMAGING": "IMAGING",
"NM CARDIAC BLOOD POOL IMAGING PLANAR": "IMAGING",
"NM CARDIAC BLOOD POOL IMAGING SPECT": "IMAGING",
"NM CARDIAC SHUNT SCAN": "IMAGING",
"NM CEA TUMOR LOCALIZATION": "IMAGING",
"NM CISTERNOGRAM": "IMAGING",
"NM CISTERNOGRAM PLANAR": "IMAGING",
"NM CISTERNOGRAM PLANAR + SPECT": "IMAGING",
"NM CISTERNOGRAM SPECT": "IMAGING",
"NM CONSULT IP": "IMAGING",
"NM CONSULT OP SERV LOW ACUITY-EST PT": "IMAGING",
"NM CONSULT OP SERV LOW ACUITY-NEW PT": "IMAGING",
"NM CONSULT OP SERV MINOR ACUITY-EST PT": "IMAGING",
"NM CONSULT OP SERV MINOR ACUITY-NEW PT": "IMAGING",
"NM CONSULT OP SERV MOD ACUITY-EST PT": "IMAGING",
"NM CONSULT OP SERV MOD ACUITY-NEW PT": "IMAGING",
"NM CONSULTATION": "IMAGING",
"NM CSF LEAK IMAGING": "IMAGING",
"NM CSF SHUNT EVAL IMAGING PLANAR": "IMAGING",
"NM CSF SHUNT EVAL IMAGING PLANAR+SPECT": "IMAGING",
"NM CSF SHUNT EVAL IMAGING PLANAR+SPECT+SPECT": "IMAGING",
"NM CSF SHUNT EVAL IMAGING SPECT": "IMAGING",
"NM CSF SHUNT EVAL IMAGING SPECT+SPECT": "IMAGING",
"NM CSF SHUNT EVALUATION": "IMAGING",
"NM ESOPHAGUS MOTILITY": "IMAGING",
"NM FIRST PASS IMAGING REST": "IMAGING",
"NM GALLIUM AND BONE SCAN": "IMAGING",
"NM GALLIUM INFLAMMATION IMAGING": "IMAGING",
"NM GALLIUM INFLAMMATION IMAGING LTD": "IMAGING",
"NM GALLIUM INFLAMMATION IMAGING LTD W SPECT": "IMAGING",
"NM GALLIUM INFLAMMATION IMAGING LTD W SPECT+SPECT": "IMAGING",
"NM GALLIUM INFLAMMATION IMAGING WB": "IMAGING",
"NM GALLIUM INFLAMMATION IMAGING WB W SPECT": "IMAGING",
"NM GALLIUM LTD AND BONE SCAN LTD": "IMAGING",
"NM GALLIUM LTD AND BONE SCAN LTD 3 PHASE": "IMAGING",
"NM GALLIUM LTD W SPECT AND BONE SCAN 3 PHASE W SPECT": "IMAGING",
"NM GALLIUM LTD W SPECT AND BONE SCAN LTD W SPECT": "IMAGING",
"NM GALLIUM TUMOR LOCALIZATION": "IMAGING",
"NM GALLIUM WB AND BONE SCAN 3 PHASE": "IMAGING",
"NM GALLIUM WB AND BONE SCAN WB": "IMAGING",
"NM GALLIUM WB W SPECT AND BONE SCAN 3 PHASE W SPECT": "IMAGING",
"NM GALLIUM WB W SPECT+SPECT AND BONE SCAN WB W SPECT+SPECT": "IMAGING",
"NM GALLIUN WB W SPECT AND BONE SCAN WB W SPECT": "IMAGING",
"NM GASTRIC EMPTYING": "IMAGING",
"NM GASTROESOPHAGEAL REFLUX STUDY": "IMAGING",
"NM GATED BLOOD POOL IMAGING SPECT": "IMAGING",
"NM GI BLOOD LOSS": "IMAGING",
"NM HEPATOBILIARY": "IMAGING",
"NM HEPATOBILIARY W QUANTITATIVE MEASUREMENTS": "IMAGING",
"NM INFLAM IMAG LTD/CERETEC WBC": "IMAGING",
"NM INFLAM IMAG LTD/INDUIM WBC": "IMAGING",
"NM INFLAMMATORY IMAGNG, LTD AREA": "IMAGING",
"NM INJECTION ONLY": "IMAGING",
"NM INJECTION ONLY INPATIENT": "IMAGING",
"NM INJECTION ONLY OUTPATIENT": "IMAGING",
"NM KIDNEY IMAGING MORPHOLOGY SPECT": "IMAGING",
"NM KIDNEY MORPHOLOGY": "IMAGING",
"NM LIVER SCAN ONLY": "IMAGING",
"NM LIVER SCAN W VASCULAR FLOW": "IMAGING",
"NM LIVER SPEC(RBC HEMANGIOMA)": "IMAGING",
"NM LIVER SPECT": "IMAGING",
"NM LIVER SPECT W VASCULAR FLOW": "IMAGING",
"NM LIVER SPLEEN SCAN": "IMAGING",
"NM LIVER SPLEEN SCAN W VASCULAR FLOW": "IMAGING",
"NM LUNG SCAN": "IMAGING",
"NM LUNG SCAN PERFUSION PARTICULATE": "IMAGING",
"NM LUNG SCAN QUANTITATIVE": "IMAGING",
"NM LUNG VENTILATION AEROSOL MULTIPLE": "IMAGING",
"NM LUNG VENTILATION PERFUSION AEROSOL": "IMAGING",
"NM MECKELS DIVERTICULUM": "IMAGING",
"NM MIBG TUMOR LOCALIZATION": "IMAGING",
"NM MIRALUMA TUMOR LOCALIZATION": "IMAGING",
"NM MYO PER RST/STRS PHARMACOLO": "IMAGING",
"NM MYOCARD PERF/REST & STRESS": "IMAGING",
"NM MYOCARD SPECT IMAG MULT": "IMAGING",
"NM MYOCARDIAL INFARCTION AVID SCAN": "IMAGING",
"NM MYOCARDIAL INFARCTION AVID TOMOGRAM SPECT": "IMAGING",
"NM MYOCARDIAL PERFUSION REST AND STRESS MULT-PLANAR": "IMAGING",
"NM MYOCARDIAL PERFUSION REST OR STRESS MULT-SPECT": "IMAGING",
"NM MYOCARDIAL PERFUSION REST OR STRESS MULTI": "IMAGING",
"NM MYOCARDIAL PERFUSION REST OR STRESS SINGLE": "IMAGING",
"NM MYOCARDIAL PERFUSION REST OR STRESS SINGLE-PLANAR": "IMAGING",
"NM MYOCARDIAL PERFUSION REST OR STRSS SINGLE-SPECT": "IMAGING",
"NM MYOCARDIAL PERFUSION VIABILITY PLANAR": "IMAGING",
"NM MYOCARDIAL PERFUSION VIABILITY SPECT": "IMAGING",
"NM MYOCARDIAL VIABILITY (THALLIUM) SCAN": "IMAGING",
"NM NON CARDIAC VASCULAR FLOW": "IMAGING",
"NM OCTREOTIDE TUMOR LOCALIZATION": "IMAGING",
"NM PARATHYROID INJ ONLY PROBE STUDY": "IMAGING",
"NM PARATHYROID SCAN": "IMAGING",
"NM PARATHYROID SCAN W SPECT": "IMAGING",
"NM PARATHYROID SCAN W SPECT + CT": "IMAGING",
"NM PERITONEAL VENOUS SHUNT": "IMAGING",
"NM PET MYOCARDIAL PERFUSION": "IMAGING",
"NM PLATELET SURVIVAL": "IMAGING",
"NM PROSTASCINT TUMOR LOCALIZATION": "IMAGING",
"NM PULMONARY PERF AND VENT IMAGING QUAN": "IMAGING",
"NM PULMONARY PERFUSION": "IMAGING",
"NM PULMONARY PERFUSION QUANTITATIVE": "IMAGING",
"NM PULMONARY VENT AND PERFUSION QUANTITATIVE": "IMAGING",
"NM PULMONARY VENT GASEOUS MULTI PROJ": "IMAGING",
"NM PULMONARY VENTILATION (AEROSOL OR GAS)": "IMAGING",
"NM PULMONARY VENTILATION AND PERFUSION": "IMAGING",
"NM RAD REVIEW 2ND OPINION": "IMAGING",
"NM RADIOLOGIST REVIEW OF OUTSIDE IMAGES": "IMAGING",
"NM RBC SURVIVAL": "IMAGING",
"NM RENAL FLOW FUNC W/ PHARM": "IMAGING",
"NM RENAL FLOW ONLY": "IMAGING",
"NM RENAL FLOW/FUNCT W/O PHARM": "IMAGING",
"NM RENAL FUNCTION NON-IMAGING": "IMAGING",
"NM RENAL FUNCTION ONLY": "IMAGING",
"NM RENOGRAM FLOW AND FUNCTION": "IMAGING",
"NM RENOGRAM W AND WO ACE INHIB": "IMAGING",
"NM RENOGRAM W AND WO CAPTOPRIL": "IMAGING",
"NM RENOGRAM W PHARM": "IMAGING",
"NM SALIVARY SCAN": "IMAGING",
"NM SENTINEL NODE IMAGING": "IMAGING",
"NM SENTINEL NODE IMAGING W SPECT": "IMAGING",
"NM SENTINEL NODE INJECTION ONLY": "IMAGING",
"NM SENTINEL NODE W IMAGING": "IMAGING",
"NM SESTAMIBI TUMOR LOCALIZATION": "IMAGING",
"NM SPLEEN SCAN ONLY": "IMAGING",
"NM TESTICULAR W VASCULAR FLOW": "IMAGING",
"NM THERAPY FOR BONE CANCER": "IMAGING",
"NM THERAPY FOR POLYCYTHERMIA VERA": "IMAGING",
"NM THERAPY FOR THYROID CANCER": "IMAGING",
"NM THERAPY FOR THYROID METS": "IMAGING",
"NM THERAPY HYPERTHYROID INITIAL": "IMAGING",
"NM THERAPY HYPERTHYROID SUBSEQUENT": "IMAGING",
"NM THYROGEN INJECTION": "IMAGING",
"NM THYROGEN INJECTION ENDOCRINE CLINIC": "IMAGING",
"NM THYROGEN INJECTION PRE IMAGING": "IMAGING",
"NM THYROID 1 UPTAKE NO IMAGE": "IMAGING",
"NM THYROID 1 UPTAKE WITH IMAGE": "IMAGING",
"NM THYROID CA METS IMAGING": "IMAGING",
"NM THYROID CA METS IMAGING LIMITED": "IMAGING",
"NM THYROID CA METS IMAGING LIMITED W SPECT": "IMAGING",
"NM THYROID CA METS IMAGING LIMITED W SPECT+SPECT": "IMAGING",
"NM THYROID CA METS IMAGING W THYROGEN STIM": "IMAGING",
"NM THYROID CA METS IMAGING WB": "IMAGING",
"NM THYROID CA METS IMAGING WB 2+DAYS W SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WB 2+DAYS W SPECT+SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WB W SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WB W SPECT+SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WB W UPTAKE": "IMAGING",
"NM THYROID CA METS IMAGING WB W UPTAKE W SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WB W UPTAKE W SPECT+SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WHOLE BODY": "IMAGING",
"NM THYROID CA METS IMAGING WHOLE BODY UPTAKE": "IMAGING",
"NM THYROID CA METS IMAGING WHOLE BODY UPTAKE W SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WHOLE BODY W SPECT": "IMAGING",
"NM THYROID CA METS IMAGING WHOLE BODY W SPECT+ADDL SPECT": "IMAGING",
"NM THYROID MULT UPTAKE NO IMAG": "IMAGING",
"NM THYROID MULT UPTAKE W IMAGE": "IMAGING",
"NM THYROID SCAN ONLY": "IMAGING",
"NM THYROID UPTAKE AND SCAN MULTIPLE": "IMAGING",
"NM THYROID UPTAKE AND SCAN SINGLE": "IMAGING",
"NM THYROID UPTAKE ONLY MULTIPLE": "IMAGING",
"NM THYROID UPTAKE ONLY SINGLE": "IMAGING",
"NM TUMOR DESTRUCTION W YTTRIUM-90": "IMAGING",
"NM TUMOR IMAGING WHOLE BODY": "IMAGING",
"NM TUMOR LOC MULTIPLE AREAS": "IMAGING",
"NM TUMOR LOC SPECT": "IMAGING",
"NM TUMOR LOC WB 2+DAY W SPECT PLUS ADDL SPECT": "IMAGING",
"NM TUMOR LOC WB W SPECT PLUS ADDL SPECT": "IMAGING",
"NM TUMOR LOC WHOLE BODY 2+ DAYS W SPECT": "IMAGING",
"NM TUMOR LOC WHOLE BODY 2+DAYS": "IMAGING",
"NM TUMOR LOC WHOLE BODY W SPECT": "IMAGING",
"NM TUMOR LOCALIZATION 1 DAY WITH SPECT": "IMAGING",
"NM TUMOR LOCALIZATION LIMITED": "IMAGING",
"NM TUMOR LOCALIZATION LIMITED WITH SPECT": "IMAGING",
"NM TUMOR LOCALIZATION SPECT": "IMAGING",
"NM TUMOR LOCALIZATION SPECT WITH SPECT": "IMAGING",
"NM TUMOR LOCALIZATION WB 1 DAY": "IMAGING",
"NM TUMOR LOCALIZATION WB 2+ DAYS": "IMAGING",
"NM TUMOR LOCALIZATION WB 2+ DAYS WITH SPECT": "IMAGING",
"NM TUMOR LOCALIZATION WHOLE BODY": "IMAGING",
"NM TUMOR LOCALIZATION WHOLE BODY 2 + DAYS": "IMAGING",
"NM TUMOR WHOLEBODY SAMEDAY IMA": "IMAGING",
"NM UNLISTED": "IMAGING",
"NM VENOUS THROMBOSIS LEFT": "IMAGING",
"NM VENOUS THROMBOSIS RIGHT": "IMAGING",
"NM VOIDING CYSTOGRAM": "IMAGING",
"NM WBC AND BONE SCAN": "IMAGING",
"NM WBC LTD AND BONE SCAN LTD": "IMAGING",
"NM WBC LTD AND BONE SCAN LTD FLOW": "IMAGING",
"NM WBC LTD W SPECT AND BONE SCAN FLOW W SPECT": "IMAGING",
"NM WBC LTD W SPECT AND BONE SCAN LTD W SPECT": "IMAGING",
"NM WBC WB AND BONE SCAN FLOW": "IMAGING",
"NM WBC WB AND BONE SCAN WB": "IMAGING",
"NM WBC WB W SPECT AND BONE SCAN FLOW W SPECT": "IMAGING",
"NM WBC WB W SPECT AND BONE SCAN WB W SPECT": "IMAGING",
"NM XOFIGO THERAPY 1": "IMAGING",
"NM XOFIGO THERAPY 2": "IMAGING",
"NM XOFIGO THERAPY 3": "IMAGING",
"NM XOFIGO THERAPY 4": "IMAGING",
"NM XOFIGO THERAPY 5": "IMAGING",
"NM XOFIGO THERAPY 6": "IMAGING",
"NM ZEVALIN TX ADMIN": "IMAGING",
"NON-IMAGING HEART FUNCTION": "IMAGING",
"NONHEMATO NUCLEAR THERAPY": "IMAGING",
"NRAS MUTATION ANALYSIS": "PATHOLOGY",
"NUCLEAR DIAGNOSTIC EXAM UNLISTED": "IMAGING",
"NUCLEAR JOINT THERAPY": "IMAGING",
"NUCLEAR LOCALIZATION/ABSCESS": "IMAGING",
"NUCLEAR MED DATA PROC": "IMAGING",
"NUCLEAR MEDICINE": "IMAGING",
"NUCLEAR MEDICINE DATA PROC": "IMAGING",
"NUCLEAR MEDICINE THERAPY": "IMAGING",
"NUCLEAR RX, IV ADMIN": "IMAGING",
"NUCLEAR TEAR FLOW": "IMAGING",
"OBSTRUCTIVE MATERIAL REMOVAL FROM GI TUBE": "IMAGING",
"OPHTHALMIC ULTRASOUND, B-SCAN & QUANTITATIVE A-SCAN": "IMAGING",
"PANORAMIC X-RAY OF JAWS": "IMAGING",
"PAP SMEAR, CONVENTIONAL": "PATHOLOGY",
"PAPHPV WITH GENOTYPE PATIENTS OVER 30 YEARS OLD": "PATHOLOGY",
"PARATHYROED PLANAR IMAGING WITH TOMOGRAPHIC (SPECT) AND CONCURRENTLY A": "IMAGING",
"PARATHYROID NUCLEAR IMAGING": "IMAGING",
"PARATHYROID PLANAR IMAGING WITH TOMOGRAPHIC (SPECT)": "IMAGING",
"PAROXYSMAL NOCTURNAL HEMOGLOBINURIA ANALYSIS BLOOD": "PATHOLOGY",
"PENILE VASCULAR STUDY,COMPLETE": "IMAGING",
"PERCUT MECH THROMBECTOMY, VENOUS": "IMAGING",
"PERCUT MECH THROMBECTOMY, VENOUS, REPEAT": "IMAGING",
"PERCUT PLACE BILE DRAIN CATH": "IMAGING",
"PERCUT XHEPATIC PORTO+DYNAMIC": "IMAGING",
"PERCUT XHEPATIC PORTOGRAM": "IMAGING",
"PERFUSION LUNG IMAGE W VENT 1+ IMAGES": "IMAGING",
"PERQ VERTE/SACROPLSTY, CT": "IMAGING",
"PET BRAIN IMAGING METABOLIC EVALUATION": "IMAGING",
"PET CARD,POST STR ECHOCARD MULTIPLE": "IMAGING",
"PET CARD,POST STR ECHOCARD SINGLE": "IMAGING",
"PET CARD,POST STR MYOCARD MULTIPLE": "IMAGING",
"PET CARD,POST STR MYOCARD SINGLE": "IMAGING",
"PET CARD,POST STR NUCL VENTRIC MULTI": "IMAGING",
"PET CARD,POST STR NUCL VENTRIC SINGL": "IMAGING",
"PET CARDIAC,POST CORON ANGIO MULTI": "IMAGING",
"PET CARDIAC,POST CORON ANGIO SINGLE": "IMAGING",
"PET CARDIAC,POST PREV PET MULTIPLE": "IMAGING",
"PET CARDIAC,POST PREV PET SINGLE": "IMAGING",
"PET CARDIAC,POST REST ECG MULTIPLE": "IMAGING",
"PET CARDIAC,POST REST ECG SINGLE": "IMAGING",
"PET CARDIAC,POST REST SPECT MULTIPLE": "IMAGING",
"PET CARDIAC,POST REST SPECT SINGLE": "IMAGING",
"PET CARDIAC,POST STRESS ECG MULTIPLE": "IMAGING",
"PET CARDIAC,POST STRESS ECG SINGLE": "IMAGING",
"PET CT F18 BONE SCAN": "IMAGING",
"PET CT F18 BONE SCAN LIMITED": "IMAGING",
"PET CT F18 BONE SCAN LIMITED PET REGISTRY": "IMAGING",
"PET CT F18 BONE SCAN SKULL BASE TO MID-THIGH": "IMAGING",
"PET CT F18 BONE SCAN SKULL-THIGH PET REGISTRY": "IMAGING",
"PET CT F18 BONE SCAN WHOLE BODY": "IMAGING",
"PET CT F18 BONE SCAN WHOLE BODY PET REGISTRY": "IMAGING",
"PET CT FDG": "IMAGING",
"PET CT FDG HEAD": "IMAGING",
"PET CT FDG HEAD PET REGISTRY": "IMAGING",
"PET CT FDG HEAD SCAN": "IMAGING",
"PET CT FDG MELANOMA": "IMAGING",
"PET CT FDG MELANOMA PET REGISTRY": "IMAGING",
"PET CT FDG MELANOMA SCAN": "IMAGING",
"PET CT FDG MYOCARDIAL METABOLIC": "IMAGING",
"PET CT FDG SCAN LIMITED": "IMAGING",
"PET CT FDG SCAN LIMITED PET REGISTRY": "IMAGING",
"PET CT FDG SCAN SKULL BASE TO MID-THIGH": "IMAGING",
"PET CT FDG SCAN SKULL BASE-MID THIGH PET REGISTRY": "IMAGING",
"PET CT FDG WHOLE BODY": "IMAGING",
"PET CT FDG WHOLE BODY PET REGISTRY": "IMAGING",
"PET CT INJECTION ONLY": "IMAGING",
"PET CT INJECTION ONLY INPATIENT": "IMAGING",
"PET CT INJECTION ONLY OUTPATIENT": "IMAGING",
"PET CT LIMITED AREA": "IMAGING",
"PET CT MYOCARDIAL METABOLIC PET REGISTERY": "IMAGING",
"PET CT SARCOIDOSIS": "IMAGING",
"PET CT SKULL TO MID THIGH": "IMAGING",
"PET CT WHOLE BODY": "IMAGING",
"PET FDG BRAIN METABOLIC": "IMAGING",
"PET IMAGE, FULL BODY": "IMAGING",
"PET IMAGE, LTD AREA": "IMAGING",
"PET IMAGE, SKULL-THIGH": "IMAGING",
"PET IMAGING FULL AND PARTIAL-RING PET SCANNERS ONLY": "IMAGING",
"PHOTODENSITOMETRY": "IMAGING",
"PHOTODYNAMIC THERAPY BY ENDOSCOPIC APPL OF LIGHT ": "IMAGING",
"PHOTODYNAMIC THERAPY ENDOSCOPIC APP OF LIGHT ADDT'L 15 MIN": "IMAGING",
"PHOTODYNAMIC THERAPY WITH LIGHT": "IMAGING",
"PLACEMENT OF VISCERAL EXT PROSTHEIS FOR ENDOVASCULAR REP": "IMAGING",
"PLASMA CELL PROFILE INTERPRETATION": "PATHOLOGY",
"PLASMA IRON TURNOVER": "IMAGING",
"PLASMA VOLUME, MULTIPLE": "IMAGING",
"PLASMA VOLUME, SINGLE": "IMAGING",
"PLATELET SURVIVAL": "IMAGING",
"PLATELET SURVIVAL, KINETICS": "IMAGING",
"PORTABLE ULTRASOUND,SOFT TISSU": "IMAGING",
"PRE OP WIRE LOC EACH ADDITIONAL LESION": "IMAGING",
"PRE-OP PLACE NEEDLE LOC WIRE, BREAST": "IMAGING",
"PROT ELECT 24HR INTERPRETATION": "PATHOLOGY",
"PROT ELECT URINE RANDOM INTERPRETATION": "PATHOLOGY",
"PROTEIN ELECTROPHORESIS INTERPRETATION": "PATHOLOGY",
"PROVIDE DIAG RADIONUCLIDE(S)": "IMAGING",
"PROVIDE THER RADIOPHARM(S)": "IMAGING",
"PROXIMAL EXTENS DURNG ENDOVASC RETHOR AORTA": "IMAGING",
"PULMONAR VENTILATION AND PERFUSION IMAGING": "IMAGING",
"PULMONRY VENTILATION IMAGING": "IMAGING",
"PUNC CYST ASP OF BREAST": "IMAGING",
"PUNC CYST ASP, OTHER BREAST": "IMAGING",
"PUNCTURE CYST ASPIRATION BREAST": "IMAGING",
"PUNCTURE CYST ASPIRATION OTHER BREAST": "IMAGING",
"QUANTITATIVE DIFF PULMONARY PERF INCL IMAGING WHEN PER": "IMAGING",
"QUANTITATIVE DIFF PULMONARY PERFUSION AND VENTILATION IN": "IMAGING",
"RADIATION DOSIMETRY UNLISTED": "IMAGING",
"RADIATION THERAPY MANAGEMENT": "IMAGING",
"RADIATION TX DELIVERY SUPERFICIAL OR ORTHO VOLTAGE PER DAY": "IMAGING",
"RADIOELEMENT APPLICATION SURFACE": "IMAGING",
"RADIOELEMENT HANDLING": "IMAGING",
"RADIOGRAPHIC PROC UNLISTED": "IMAGING",
"RADIOLOGIC EXAM HIP UNILATERAL W PELVIS WHEN PERFORM MINIMUM 4 VIEWS": "IMAGING",
"RADIOLOGIC EXAM HIP UNILATERAL WITH PELVIS WHEN PERFORMED 1 VIES": "IMAGING",
"RADIOLOGIC EXAM HIP UNILATERAL WITH PELVIS WHEN PERFORMED 2-3 VIEWS": "IMAGING",
"RADIOLOGIC EXAM HIPS BILATERAL W PELVIS WHEN PERFORM MINIMUM 5 VIEWS": "IMAGING",
"RADIOLOGIC EXAM HIPS BILATERAL WITH PELVIS WHEN PERFORMED 2 VIEWS": "IMAGING",
"RADIOLOGIC EXAM HIPS BILATERAL WITH PELVIS WHEN PERFORMED 3-4 VIEWS": "IMAGING",
"RADIOLOGIC EXAM SPINE ENTIRE THORACIC & LUMBAR MINIIMUM OF 6 VIEWS": "IMAGING",
"RADIOLOGIC EXAM SPINE ENTIRE THORACIC & LUMBAR ONE VIEW": "IMAGING",
"RADIOLOGIC EXAMINATION FEMUR 1 VIEW": "IMAGING",
"RADIOLOGIC EXAMINATION FEMUR MINIMUM 2 VIEWS": "IMAGING",
"RADIOLOGIC EXAMINATION SPINE ENTIRE THORACIC & LUMBAR 2 OR 3 VIEWS": "IMAGING",
"RADIOLOGIC EXAMINATION SPINE ENTIRE THORACIC & LUMBAR 4 OR 5 VIEWS": "IMAGING",
"RADIOLOGIST REVIEW OUTSIDE FIL": "IMAGING",
"RADIOLOGY PORT IMAGES": "IMAGING",
"RADIOPHARMACEUTICAL THERAPY INTRA ARTICULAR ADMIN": "IMAGING",
"RADIOPHARMACEUTICAL, DIAGNOSTIC, FOR BETA-AMYLOID POSITR": "IMAGING",
"RADIUM/RADIOISOTOPE THERAPY UNLIST": "IMAGING",
"RADN RX DELIVERY COMPLX 11-19 MEV": "IMAGING",
"RADN RX DELIVERY COMPLX 20+ MEV": "IMAGING",
"RADN RX DELIVERY COMPLX 6-10 MEV": "IMAGING",
"RADN RX DELIVERY COMPLX =>1 MEV COMPLEX": "IMAGING",
"RADN RX DELIVERY INTERM 11-19 MEV": "IMAGING",
"RADN RX DELIVERY INTERM 20+ MEV": "IMAGING",
"RADN RX DELIVERY INTERM 6-10 MEV": "IMAGING",
"RADN RX DELIVERY INTERM =>1 MEV INTERMEDIATE": "IMAGING",
"RADN RX DELIVERY SIMPLE 11-19 MEV": "IMAGING",
"RADN RX DELIVERY SIMPLE 20+ MEV": "IMAGING",
"RADN RX DELIVERY SIMPLE 6-10 MEV": "IMAGING",
"RADN RX DELIVERY SIMPLE =>1 MEV SIMPLE": "IMAGING",
"RADN THERAPY MANAGEMENT UNLISTED": "IMAGING",
"RADN THERAPY PLANNING UNLISTED": "IMAGING",
"RADXPS IN END RPRT4FLURO PXD": "IMAGING",
"RED CELL IRON UTILIZATION": "IMAGING",
"RED CELL MASS, MULTIPLE": "IMAGING",
"RED CELL MASS, SINGLE": "IMAGING",
"RED CELL SEQUESTRATION": "IMAGING",
"RED CELL SURVIVAL KINETICS": "IMAGING",
"RED CELL SURVIVAL STUDY": "IMAGING",
"REMOVE ESOPHAGUS OBSTRUCTION": "IMAGING",
"REMOVE URETER STENT, PERCUT": "IMAGING",
"REMOVE URETERAL STENT VIA TRANSURETH": "IMAGING",
"REMOVE,OBST MATL,CVA DEV VIA SEP VEN ACC": "IMAGING",
"REMOVE,OBST MATL,CVA DEVICE VIA LUMEN": "IMAGING",
"RENAL FLOW/FUNCT IMAGE,COMBO,PHARM": "IMAGING",
"RENAL FUNCTION STUDY": "IMAGING",
"RENAL IMAGING SPECT": "IMAGING",
"RENAL IMAGING STATIC": "IMAGING",
"RENAL IMAGING WITH FLOW": "IMAGING",
"RENAL IMAGING, WITH FUNCTION": "IMAGING",
"RENAL VASCULAR FLOW EXAM": "IMAGING",
"REPAIR,ILIAC ANRYSM/PSEUDO/AV MALF/TRAUM": "IMAGING",
"REPEAT HYPERTHYROID THERAPY": "IMAGING",
"REPLACE CV CATH, CATHETER ONLY W SUBQ PUMP OR PORT": "IMAGING",
"REPLACE CV CATH, COMPLETE, TUNNELED, W SUBQ PORT OR PUMP": "IMAGING",
"REPLACE CV CATH, COMPLETE, TUNNELED, W/O SUBQ PORT OR PUMP": "IMAGING",
"REPLACE DUODENOSTOMY/JEJUNOSTOMY TUBE PERCUTANEOUS": "IMAGING",
"REPLACE GASTROSTOMY/CECOSTOMY TUBE PERCUTANEOUS": "IMAGING",
"REPLACE PICC W/O PORT OR PUMP": "IMAGING",
"REPLACE PICC W PORT OR PUMP": "IMAGING",
"REPLACEMENT GASTRO-JEJUNOSTOMY TUBE PERCUTANEOUS": "IMAGING",
"REPOSITION VENOUS CATHETER": "IMAGING",
"RESP NUCLEAR EXAM UNLISTED": "IMAGING",
"RESPIRATORY MOTION MANAGEMENT SIMULATION ": "IMAGING",
"REUSE": "IMAGING",
"REVIS TRANSVEN INTRAHEP PORTOSYS SHUNT": "IMAGING",
"RHYTHM STRIP": "IMAGING",
"RPRT BONE SCINT XREF W XRAY": "IMAGING",
"SALIVARY GLAND FUNCTION EXAM": "IMAGING",
"SALIVARY GLAND IMAGING": "IMAGING",
"SCR MAMMO BIL 2-VIEW STUDY EACH BREAST INCL COMPUTER AIDED DETECTION": "IMAGING",
"SCREEN SINUSES": "IMAGING",
"SCREENING ABI": "IMAGING",
"SCREENING DIGITAL BREAST TOMOSYNTHESIS BILATERAL ": "IMAGING",
"SCREENING MAMMOGRAPHY BI 2-VIEW BREAST INC CAD": "IMAGING",
"SCREENING ORBITS FOR MRI": "IMAGING",
"SCREENING VASCULAR": "IMAGING",
"SERIAL SALIVARY IMAGING": "IMAGING",
"SERUM IMMUNOFIXATION INTERPRETATION": "PATHOLOGY",
"SET RADN THERAPY FIELD 3D RECON": "IMAGING",
"SET UP PORT XRAY EQUIPMENT": "IMAGING",
"SHUNT ADDL ACCESS W/RX ": "IMAGING",
"SHUNT EVAL COMPLETE ": "IMAGING",
"SOMATOSENSORY EVOKED POTENTIAL": "IMAGING",
"SOMATOSENSORY LOWER LIMB": "IMAGING",
"SOMATOSENSORY UPPER LIMB": "IMAGING",
"SONO EXAM KIDNEY TRANSPLANT": "IMAGING",
"SONO EXAM,INFANT HIPS,STATIC.LTD": "IMAGING",
"SONO EYE A-SCAN": "IMAGING",
"SONO EYE B-SCAN": "IMAGING",
"SONO EYE BIOMETRY": "IMAGING",
"SONO EYE BIOMETRY W LENS CALC": "IMAGING",
"SONO EYE F.B. LOCALIZATN": "IMAGING",
"SONO EYE WATER BATH B-SCAN": "IMAGING",
"SONO FETAL HEART": "IMAGING",
"SONO FETAL HEART DOPPLER": "IMAGING",
"SONO FETAL HEART F/U": "IMAGING",
"SONO FETAL HRT DOPPL F/U": "IMAGING",
"SONO GUIDE ARTERY REPAIR": "IMAGING",
"SONO GUIDE CHEST TAP": "IMAGING",
"SONO GUIDE CHOR VILL SAMPLING": "IMAGING",
"SONO GUIDE CYST ASPIRATN": "IMAGING",
"SONO GUIDE HEART BIOPSY": "IMAGING",
"SONO GUIDE INTRAUTER XFUSN": "IMAGING",
"SONO GUIDE OVA ASPIRATION": "IMAGING",
"SONO GUIDE PERICARD TAP": "IMAGING",
"SONO GUIDE RADIOTHER FLD": "IMAGING",
"SONO GUIDE RADIOTHER FLD B-SCAN": "IMAGING",
"SONOHYSTEROGRAM DONE IN OB DEP": "IMAGING",
"SPE MONOCLONAL GAMMOPATHY FOLLOW UP INTERPRETATION": "PATHOLOGY",
"SPE MONOCLONAL GAMMOPATHY SCREEN INTERPRETATION": "PATHOLOGY",
"SPE WITH IMMUNOFIXATION INTERPRETATION": "PATHOLOGY",
"SPECIAL RADIATION TREATMENT": "IMAGING",
"SPECIAL X-RAY SUBTRACTN STUDY": "IMAGING",
"SPEECH EVALUATION, COMPLEX": "IMAGING",
"SPLEEN IMAGING": "IMAGING",
"STEREOSCOPIC X-RAY GUIDANCE FOR LOCAL OF TARGET VOLUME ": "IMAGING",
"STEREOTACTIC BODY RADIATION THERAPY TREATMENT MGMT": "IMAGING",
"STEREOTACTIC RADN TRMT CEREBRL": "IMAGING",
"SUPPLY STRONTIUM-89 CL, PER MCI": "IMAGING",
"TC-99M FROM NON-HIGHLY ENRICHED URANIUM SOURCE, FULL COST RECOVERY ADD": "IMAGING",
"TC99 TETROFOSMIN (MYOVIEW) PER STUDY DOSE": "IMAGING",
"TECHNETIUM TC-99M EXAMETAZIME LABELED AUTOLOGOUS ": "IMAGING",
"TEE FOR MONITORING PURPOSES": "IMAGING",
"TESTICULAR IMAGING": "IMAGING",
"TESTICULAR IMAGING & FLOW": "IMAGING",
"THINPREP PAP TEST NO HPV": "PATHOLOGY",
"THINPREP PAP TEST WITH HPV REFLEX": "PATHOLOGY",
"THINPREP PAP TEST WITH HPV REGARDLESS": "PATHOLOGY",
"THROAT X-RAY & FLUOROSCOPY": "IMAGING",
"THROMBECTOMY,ARTERIOVENOUS FISTULA": "IMAGING",
"THYROID ABLATION": "IMAGING",
"THYROID ABLATION, CARCINOMA": "IMAGING",
"THYROID IMAGING": "IMAGING",
"THYROID IMAGING WITH FLOW": "IMAGING",
"THYROID IMAGING WITH SINGLE OR MULTIPLE UPTAKE(S) QUANTITATIVE MEASURE": "IMAGING",
"THYROID MET IMAGING ADDN LTD": "IMAGING",
"THYROID MET IMAGING LTD": "IMAGING",
"THYROID MET IMAGING MULTP": "IMAGING",
"THYROID MET UPTAKE": "IMAGING",
"THYROID METASTATIC THERAPY": "IMAGING",
"THYROID SUPPRESS/STIMUL": "IMAGING",
"THYROID UPTAKE SINGLE OR MULTIPLE QUANTITATIVE MEASUREMENT(S)": "IMAGING",
"THYROID,WHOLE BODY SCAN": "IMAGING",
"TOTAL BODY IRON ESTIMATION": "IMAGING",
"TRANSCATH STENT, CCA W/O EPS": "IMAGING",
"TRANSCRANIAL DOPPLER": "IMAGING",
"TRANSHEPATIC BILE DRAINAGE": "IMAGING",
"TRANSLUMINAL PERIPHERAL ATHERECTOMY BRACHIOCEPHALIC TRUNK AND BRANCHES": "IMAGING",
"TUMOR IMAGING (PET)": "IMAGING",
"TUMOR IMAGING SPECT": "IMAGING",
"TUMOR IMAGING, LIMITED AREA": "IMAGING",
"TUMOR IMAGING, MULT AREAS": "IMAGING",
"UG GUIDE UPPER EXT TENDON SHEATH-LIGAMENT LEFT": "IMAGING",
"ULTRASOUND AAA SCREENING": "IMAGING",
"ULTRASOUND ABDOMEN COMPLETE": "IMAGING",
"ULTRASOUND BREAST": "IMAGING",
"ULTRASOUND BREAST UNILATERAL INC AXILLA WHEN PERF LIMIT ": "IMAGING",
"ULTRASOUND BREAST UNILATERAL WITH IMAGE DOC INC AXILLA ": "IMAGING",
"ULTRASOUND CHEST": "IMAGING",
"ULTRASOUND EX SPINAL CANAL": "IMAGING",
"ULTRASOUND EXAM FOLLOW-UP": "IMAGING",
"ULTRASOUND GUIDANCE MONITOR PARENCHYMAL TISSUE ABL PRO": "IMAGING",
"ULTRASOUND GUIDE AMNIOCENTESIS": "IMAGING",
"ULTRASOUND HEAD INFANT": "IMAGING",
"ULTRASOUND INFANT HIP/DYNAMIC": "IMAGING",
"ULTRASOUND PELVIC COMP": "IMAGING",
"ULTRASOUND PELVIS LIMITED": "IMAGING",
"ULTRASOUND PREG FU OR REPEAT": "IMAGING",
"ULTRASOUND PREG MULT GEST": "IMAGING",
"ULTRASOUND PREG MULT GESTATION": "IMAGING",
"ULTRASOUND PREGNANCY COMP": "IMAGING",
"ULTRASOUND PREGNANCY LTD": "IMAGING",
"ULTRASOUND SCROTUM/TESTICLES": "IMAGING",
"ULTRASOUND THYROID": "IMAGING",
"ULTRASOUND TRANSRECTAL": "IMAGING",
"ULTRASOUND,RENAL AORTA": "IMAGING",
"ULTRASOUND,TRANSRECTAL": "IMAGING",
"UPE MONOCLONAL 24HR INTERPRETATION": "PATHOLOGY",
"UPE MONOCLONAL INTERPRETATION": "PATHOLOGY",
"URETERAL REFLUX STUDY": "IMAGING",
"URINARY BLADDER RETENTION": "IMAGING",
"US ABD LIMITED SINGLE ORGAN": "IMAGING",
"US ABDOMEN AND DUPLEX COMPLETE": "IMAGING",
"US ABDOMEN COMPLETE": "IMAGING",
"US ABDOMEN LIMITED": "IMAGING",
"US ABDOMEN LIMITED ( SGL ORGAN, QUANDRANT, FU)": "IMAGING",
"US ABDOMEN PELVIS VASCULAR DUPLEX STUDY COMPLETE": "IMAGING",
"US ABDOMEN PELVIS VASCULAR DUPLEX STUDY LIMITED": "IMAGING",
"US ABDOMINAL AORTA REAL TIME SCREEN STUDY AAA": "IMAGING",
"US ABI MULTIPLE LEVELS NO STRESS": "IMAGING",
"US ABI REST AND STRESS BILATERAL": "IMAGING",
"US ALLENS UPPER EXTREMITY ARTERIES DUPLEX BILATERAL": "IMAGING",
"US ALLENS UPPER EXTREMITY ARTERIES DUPLEX LEFT": "IMAGING",
"US ALLENS UPPER EXTREMITY ARTERIES DUPLEX RIGHT": "IMAGING",
"US ALLENS UPPER EXTREMITY SEG PRESSURES": "IMAGING",
"US ANKLE / BRACHIAL 1 OR 2 LEVEL EXTREMITY BILATERAL": "IMAGING",
"US ANKLE / BRACHIAL 1 OR 2 LEVEL EXTREMITY LEFT": "IMAGING",
"US ANKLE / BRACHIAL 1 OR 2 LEVEL EXTREMITY RIGHT": "IMAGING",
"US AORTA COMPLETE": "IMAGING",
"US AORTA LIMITED": "IMAGING",
"US AORTA LTD": "IMAGING",
"US AORTA SCREENING": "IMAGING",
"US APPENDIX": "IMAGING",
"US ART GRAFT VEL BILAT/MF ONLY": "IMAGING",
"US ART GRAFT VEL LEFT(MF ONLY)": "IMAGING",
"US ART GRAFT VEL RT(MF ONLY)": "IMAGING",
"US ARTERIAL LWR EXT, BILAT": "IMAGING",
"US ARTERIAL LWR EXT, UNILAT": "IMAGING",
"US ARTERIAL UPPR EXT, UNILAT": "IMAGING",
"US ASCITES": "IMAGING",
"US BIOPHYSICAL PROFILE WITH NON STRESS TESTING": "IMAGING",
"US BIOPHYSICAL PROFILE WO NON STRESS TESTING": "IMAGING",
"US BLADDER ONLY": "IMAGING",
"US BREAST BILAT": "IMAGING",
"US BREAST BILATERAL": "IMAGING",
"US BREAST COMPLETE ALL 4 QUADRANTS BILATERAL": "IMAGING",
"US BREAST COMPLETE ALL 4 QUADRANTS LEFT": "IMAGING",
"US BREAST COMPLETE ALL 4 QUADRANTS RIGHT": "IMAGING",
"US BREAST LEFT": "IMAGING",
"US BREAST LIMITED 1-3 QUADRANTS BILATERAL": "IMAGING",
"US BREAST LIMITED 1-3 QUADRANTS LEFT": "IMAGING",
"US BREAST LIMITED 1-3 QUADRANTS RIGHT": "IMAGING",
"US BREAST RIGHT": "IMAGING",
"US CAROTID COMPLETE BILAT": "IMAGING",
"US CAROTID COMPLETE LT": "IMAGING",
"US CAROTID COMPLETE RT": "IMAGING",
"US CAROTID DUPLEX BILATERAL": "IMAGING",
"US CAROTID DUPLEX LEFT": "IMAGING",
"US CAROTID DUPLEX RIGHT": "IMAGING",
"US CHEST": "IMAGING",
"US CHEST LIMITED": "IMAGING",
"US DOPPLER VELOCIMETRY FETAL ARTERY MIDDLE": "IMAGING",
"US DOPPLER VELOCIMETRY FETAL ARTERY UMBILICAL": "IMAGING",
"US DUP LOW EXT ART COM/BIL GH": "IMAGING",
"US DUP LOW EXT ART LTD LFT/GH": "IMAGING",
"US DUP LOW EXT ART LTD RT/GH": "IMAGING",
"US DUP UP EXT ART LTD LEFT": "IMAGING",
"US DUP UP EXT ART LTD RIGHT": "IMAGING",
"US DUPLEX HEMODIALYSIS ACCESS": "IMAGING",
"US DUPLEX HEMODYALYSIS ACCESS": "IMAGING",
"US EXAM FOLLOW UP": "IMAGING",
"US EXT VENOUS DOPPLER LEFT": "IMAGING",
"US EXT VENOUS DOPPLER RIGHT": "IMAGING",
"US EXTREMITY": "IMAGING",
"US EXTREMITY LEFT": "IMAGING",
"US EXTREMITY NONVASC REAL TIME COMPLETE": "IMAGING",
"US EXTREMITY NONVASCULAR LIMITED, ANATOMIC SPECIFIC": "IMAGING",
"US EXTREMITY RIGHT": "IMAGING",
"US EXTREMITY VENOUS DOPPLER BILATERAL": "IMAGING",
"US EXTREMITY VENOUS DOPPLER LEFT": "IMAGING",
"US EXTREMITY VENOUS DOPPLER RIGHT": "IMAGING",
"US EXTREMITY VENOUS DOPPLER UNILATERAL": "IMAGING",
"US EXTREMITY VENOUS DUPLEX INSUFFICIENCY BILATERAL": "IMAGING",
"US EXTREMITY VENOUS DUPLEX INSUFFICIENCY LEFT": "IMAGING",
"US EXTREMITY VENOUS DUPLEX INSUFFICIENCY RIGHT": "IMAGING",
"US EXTREMITY VENOUS DUPLEX MAPPING BILATERAL": "IMAGING",
"US EXTREMITY VENOUS DUPLEX MAPPING LEFT": "IMAGING",
"US EXTREMITY VENOUS DUPLEX MAPPING RIGHT": "IMAGING",
"US FETAL BIOPHY PRO W/O STRESS": "IMAGING",
"US FETAL BIOPHYSICAL PRO W/STR": "IMAGING",
"US FETAL CORD PUNCTURE PRENATAL": "IMAGING",
"US FETAL HEART COMPLETE": "IMAGING",
"US FETAL HEART COMPLETE AND DUPLEX": "IMAGING",
"US FETAL HEART FOLLOW UP": "IMAGING",
"US FETAL HEART FOLLOW UP AND DUPLEX": "IMAGING",
"US FETAL HEART FOLLOW UP W COLOR FLOW": "IMAGING",
"US FETAL HEART FOLLOW UP W COLOR FLOW AND DUPLEX": "IMAGING",
"US FETAL HEART W COLOR FLOW": "IMAGING",
"US FETAL HEART W COLOR FLOW AND DUPLEX": "IMAGING",
"US FOLLICULAR STUDY": "IMAGING",
"US FOLLICULAR VAGINAL": "IMAGING",
"US GALLBLADDER": "IMAGING",
"US GUID BRST CYS ASP W/O CYTOL": "IMAGING",
"US GUID/BRST CYST/ASPI W/CYTOL": "IMAGING",
"US GUIDANCE AMNIOCENTESIS DIAGNOSTIC": "IMAGING",
"US GUIDANCE AMNIOCENTESIS THERAPEUTIC DONE IN MFM": "IMAGING",
"US GUIDANCE CORDOCENTESIS INTRAUTERINE": "IMAGING",
"US GUIDANCE CORDOCENTESIS INTRAUTERINE W FETAL TRANSFUSN": "IMAGING",
"US GUIDANCE ENDOVENOUS LASER ABLATION": "IMAGING",
"US GUIDANCE FOR EGG RETRIEVAL OB DEPT": "IMAGING",
"US GUIDANCE FOR EMBRYO TRANSFER OB DEPT": "IMAGING",
"US GUIDANCE INTRAOPERATIVE": "IMAGING",
"US GUIDANCE PHLEBECTOMY 10-20 INCISIONS": "IMAGING",
"US GUIDANCE PHLEBECTOMY > 20 INCISIONS": "IMAGING",
"US GUIDANCE SCLEROTHERAPY MULTIPLE VEINS": "IMAGING",
"US GUIDANCE SCLEROTHERAPY SINGLE VEIN": "IMAGING",
"US GUIDANCE SCLEROTHERAPY SPIDER VEIN LEG": "IMAGING",
"US GUIDANCE THROMBIN INJECTION": "IMAGING",
"US GUIDE ANKLE ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE ANKLE ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE ANKLE ASPIRATION LEFT": "IMAGING",
"US GUIDE ANKLE ASPIRATION RIGHT": "IMAGING",
"US GUIDE ANKLE INJECTION LEFT": "IMAGING",
"US GUIDE ANKLE INJECTION RIGHT": "IMAGING",
"US GUIDE BREAST ASP/BIOPSY/WIRE LOC BILATERAL": "IMAGING",
"US GUIDE BREAST BIOPSY 2 LESIONS BILATERAL": "IMAGING",
"US GUIDE BREAST BIOPSY 2 LESIONS LEFT": "IMAGING",
"US GUIDE BREAST BIOPSY 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST BIOPSY SINGLE LESION BILATERAL": "IMAGING",
"US GUIDE BREAST BIOPSY SINGLE LESION LEFT": "IMAGING",
"US GUIDE BREAST BIOPSY SINGLE LESION RIGHT": "IMAGING",
"US GUIDE BREAST BX 1 LESION LEFT AND BX 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST BX 1 LESION LEFT AND FNA 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST BX 1 LESION LEFT AND RIGHT": "IMAGING",
"US GUIDE BREAST BX 2 LESION LEFT AND FNA 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST BX 2 LESIONS LEFT AND 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST BX 2 LESIONS LEFT AND BX 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION 2 LESIONS BILATERAL": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION 2 LESIONS LEFT": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION ONLY LEFT": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION ONLY LEFT AND RIGHT": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION ONLY RIGHT": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION SINGLE LESION BILATERAL": "IMAGING",
"US GUIDE BREAST CYST ASPIRATION SINGLE LESION LEFT": "IMAGING",
"US GUIDE BREAST FNA 1 LESION LEFT AND 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST FNA 1 LESION LEFT AND BX 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST FNA 1 LESION LEFT AND BX 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST FNA 1 LESION LEFT AND FNA 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST FNA 2 LESIONS BILATERAL": "IMAGING",
"US GUIDE BREAST FNA 2 LESIONS LEFT": "IMAGING",
"US GUIDE BREAST FNA 2 LESIONS LEFT AND 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST FNA 2 LESIONS LEFT AND 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST FNA 2 LESIONS LEFT AND BX 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST FNA 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST FNA SINGLE LESION BILATERAL": "IMAGING",
"US GUIDE BREAST FNA SINGLE LESION LEFT": "IMAGING",
"US GUIDE BREAST FNA SINGLE LESION RIGHT": "IMAGING",
"US GUIDE BREAST FNA/BIOPSY/WIRE LOC LEFT": "IMAGING",
"US GUIDE BREAST FNA/BIOPSY/WIRE LOC LEFT AND RIGHT": "IMAGING",
"US GUIDE BREAST FNA/BIOPSY/WIRE LOC RIGHT": "IMAGING",
"US GUIDE BREAST PLACE LOC DEVICE 1 LESION LEFT AND RIGHT": "IMAGING",
"US GUIDE BREAST PLACE LOC DEVICE 1 LESION RIGHT AND 2 LESIONS LEFT": "IMAGING",
"US GUIDE BREAST PLACE LOC DEVICE 2 LESIONS LEFT AND 1 LESION RIGHT": "IMAGING",
"US GUIDE BREAST PLACE LOC DEVICE 2 LESIONS LEFT AND 2 LESION RIGHT": "IMAGING",
"US GUIDE BREAST PLACEMENT LOC DEVICE 2 LESIONS BILATERAL": "IMAGING",
"US GUIDE BREAST PLACEMENT LOC DEVICE 2 LESIONS LEFT": "IMAGING",
"US GUIDE BREAST PLACEMENT LOC DEVICE 2 LESIONS RIGHT": "IMAGING",
"US GUIDE BREAST PLACEMENT LOC DEVICE SINGLE LESION BILATERAL": "IMAGING",
"US GUIDE BREAST PLACEMENT LOC DEVICE SINGLE LESION LEFT": "IMAGING",
"US GUIDE BREAST PLACEMENT LOC DEVICE SINGLE LESION RIGHT": "IMAGING",
"US GUIDE CHEST TAP/THORACENTES": "IMAGING",
"US GUIDE CYST ASPIRATION SINGLE LESION RIGHT": "IMAGING",
"US GUIDE ELBOW ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE ELBOW ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE ELBOW ASPIRATION LEFT": "IMAGING",
"US GUIDE ELBOW ASPIRATION RIGHT": "IMAGING",
"US GUIDE ELBOW INJECTION LEFT": "IMAGING",
"US GUIDE ELBOW INJECTION RIGHT": "IMAGING",
"US GUIDE FINGER ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE FINGER ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE FINGER ASPIRATION LEFT": "IMAGING",
"US GUIDE FINGER ASPIRATON RIGHT": "IMAGING",
"US GUIDE FINGER INJECTION LEFT": "IMAGING",
"US GUIDE FINGER INJECTION RIGHT": "IMAGING",
"US GUIDE FOOT ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE FOOT ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE FOOT ASPIRATION LEFT": "IMAGING",
"US GUIDE FOOT ASPIRATION RIGHT": "IMAGING",
"US GUIDE FOOT INJECTION LEFT": "IMAGING",
"US GUIDE FOOT INJECTION RIGHT": "IMAGING",
"US GUIDE HAND ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE HAND ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE HAND ASPIRATION LEFT": "IMAGING",
"US GUIDE HAND ASPIRATION RIGHT": "IMAGING",
"US GUIDE HAND DUPUYTRENS CONTRACTURE LEFT": "IMAGING",
"US GUIDE HAND DUPUYTRENS CONTRACTURE RIGHT": "IMAGING",
"US GUIDE HAND INJECTION LEFT": "IMAGING",
"US GUIDE HAND INJECTION RIGHT": "IMAGING",
"US GUIDE HIP ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE HIP ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE HIP ASPIRATION LEFT": "IMAGING",
"US GUIDE HIP ASPIRATION RIGHT": "IMAGING",
"US GUIDE HIP INJECTION LEFT": "IMAGING",
"US GUIDE HIP INJECTION RIGHT": "IMAGING",
"US GUIDE INTRATHECAL PUMP CHECK REFILL": "IMAGING",
"US GUIDE KNEE ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE KNEE ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE KNEE ASPIRATION RIGHT": "IMAGING",
"US GUIDE KNEE ASPIRATON LEFT": "IMAGING",
"US GUIDE KNEE INJECTION LEFT": "IMAGING",
"US GUIDE KNEE INJECTION RIGHT": "IMAGING",
"US GUIDE LOWER EXT SINGLE OR MULTI TRIGGER 1-2 MUSCLES LEFT": "IMAGING",
"US GUIDE LOWER EXT SINGLE OR MULTI TRIGGER 1-2 MUSCLES RIGHT": "IMAGING",
"US GUIDE LOWER EXT SINGLE OR MULTI TRIGGER 3+ MUSCLES LEFT": "IMAGING",
"US GUIDE LOWER EXT SINGLE OR MULTI TRIGGER 3+MUSCLES RIGHT": "IMAGING",
"US GUIDE LOWER EXT SINGLE TENDON ORGIN LEFT": "IMAGING",
"US GUIDE LOWER EXT SINGLE TENDON ORGIN RIGHT": "IMAGING",
"US GUIDE LOWER EXT TENDON SHEATH-LIGAMENT LEFT": "IMAGING",
"US GUIDE LOWER EXT TENDON SHEATH-LIGAMENT RIGHT": "IMAGING",
"US GUIDE LOWER EXTREMITY JOINT INJ/ASP": "IMAGING",
"US GUIDE LOWER EXTREMITY TENDON OR TRIGGER PT INJ LEFT": "IMAGING",
"US GUIDE LOWER EXTREMITY TENDON OR TRIGGER PT INJ RIGHT": "IMAGING",
"US GUIDE LYMPH ASPIRATION": "IMAGING",
"US GUIDE LYMPH ASPIRATION/BIOPSY": "IMAGING",
"US GUIDE LYMPH BIOPSY DEEP": "IMAGING",
"US GUIDE LYMPH BIOPSY SUPERFICIAL": "IMAGING",
"US GUIDE MORTONS NEUROMA LEFT": "IMAGING",
"US GUIDE MORTONS NEUROMA RIGHT": "IMAGING",
"US GUIDE NEEDLE BIOPSY": "IMAGING",
"US GUIDE OVA ASPIRATION": "IMAGING",
"US GUIDE PL METALLIC TISS MARK": "IMAGING",
"US GUIDE SHOULDER ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE SHOULDER ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE SHOULDER ASPIRATION LEFT": "IMAGING",
"US GUIDE SHOULDER ASPIRATION RIGHT": "IMAGING",
"US GUIDE SHOULDER INJECTION LEFT": "IMAGING",
"US GUIDE SHOULDER INJECTION RIGHT": "IMAGING",
"US GUIDE THYROID BX EA ADDL LESION": "IMAGING",
"US GUIDE THYROID LESION ASPIRATION": "IMAGING",
"US GUIDE TOE ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE TOE ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE TOE ASPIRATION LEFT": "IMAGING",
"US GUIDE TOE ASPIRATION RIGHT": "IMAGING",
"US GUIDE TOE INJECTION LEFT": "IMAGING",
"US GUIDE TOE INJECTION RIGHT": "IMAGING",
"US GUIDE TRANSFUSION FETAL INTERAUTER": "IMAGING",
"US GUIDE UPPER EXT SINGLE OR MULTI TRIGGER 1-2 MUSCLES LEFT": "IMAGING",
"US GUIDE UPPER EXT SINGLE OR MULTI TRIGGER 1-2 MUSCLES RIGHT": "IMAGING",
"US GUIDE UPPER EXT SINGLE OR MULTI TRIGGER 3+ MUSCLES LEFT": "IMAGING",
"US GUIDE UPPER EXT SINGLE OR MULTI TRIGGER 3+ MUSCLES RIGHT": "IMAGING",
"US GUIDE UPPER EXT SINGLE TENDON ORGIN LEFT": "IMAGING",
"US GUIDE UPPER EXT SINGLE TENDON ORGIN RIGHT": "IMAGING",
"US GUIDE UPPER EXT TENDON SHEATH-LIGAMENT RIGHT": "IMAGING",
"US GUIDE UPPER EXTREMITY JOINT INJ/ASP": "IMAGING",
"US GUIDE UPPER EXTREMITY TENDON OR TRIGGER PT INJ LEFT": "IMAGING",
"US GUIDE UPPER EXTREMITY TENDON OR TRIGGER PT INJ RIGHT": "IMAGING",
"US GUIDE WRIST ASPIRATION AND INJECTION LEFT": "IMAGING",
"US GUIDE WRIST ASPIRATION AND INJECTION RIGHT": "IMAGING",
"US GUIDE WRIST ASPIRATION LEFT": "IMAGING",
"US GUIDE WRIST ASPIRATION RIGHT": "IMAGING",
"US GUIDE WRIST CARPAL TUNEL LEFT": "IMAGING",
"US GUIDE WRIST CARPAL TUNEL RIGHT": "IMAGING",
"US GUIDE WRIST INJECTION LEFT": "IMAGING",
"US GUIDE WRIST INJECTION RIGHT": "IMAGING",
"US GUIDED ABSCESS DRAIN": "IMAGING",
"US GUIDED BREAST ASP/BIOPSY/WIRE LOC": "IMAGING",
"US GUIDED BREAST CORE BIOPSY": "IMAGING",
"US GUIDED BRST LESION ASP/BX/WIRE LOC": "IMAGING",
"US GUIDED CHORIONIC VILLUS SAMPLING": "IMAGING",
"US GUIDED COMPRESSION REPAIR OF ARTERIOVENOUS FISTULAE": "IMAGING",
"US GUIDED CYST ASPIRATION": "IMAGING",
"US GUIDED INTRAOPERATIVE": "IMAGING",
"US GUIDED LIVER BIOPSY": "IMAGING",
"US GUIDED NEEDLE PLACEMENT": "IMAGING",
"US GUIDED PARACENTESIS": "IMAGING",
"US GUIDED THORACENTESIS": "IMAGING",
"US GUIDED THYROID BIOPSY": "IMAGING",
"US GUIDED TISSUE ABLATION": "IMAGING",
"US HEAD": "IMAGING",
"US HIPS INFANT W MANIPULATION": "IMAGING",
"US HIPS INFANT WO MANIPULATION": "IMAGING",
"US KIDNEY LTD": "IMAGING",
"US LARGE VESSELS DUPLEX COMPLETE NON EXTREMITY": "IMAGING",
"US LARGE VESSELS DUPLEX LIMITED NON EXTREMITY": "IMAGING",
"US LIVER / GALLBLADDER / PANCREAS": "IMAGING",
"US LIVER TRANSPLANT": "IMAGING",
"US LIVER TRANSPLANT COMPLETE": "IMAGING",
"US LIVER TRANSPLANT LIMITED": "IMAGING",
"US LIVER W DOPPLER COMPLETE": "IMAGING",
"US LIVER W DOPPLER LIMITED": "IMAGING",
"US LIVER WO DOPPLER": "IMAGING",
"US LOWER EXTREMITY ABI MULTIPLE LEVELS NO STRESS": "IMAGING",
"US LOWER EXTREMITY ARTERIES DUPLEX BILATERAL": "IMAGING",
"US LOWER EXTREMITY ARTERIES DUPLEX LEFT": "IMAGING",
"US LOWER EXTREMITY ARTERIES DUPLEX RIGHT": "IMAGING",
"US LOWER EXTREMITY ARTERIES ISCHEMIC LEVEL 1 BILATERAL": "IMAGING",
"US LOWER EXTREMITY ARTERIES ISCHEMIC LEVEL 1 LEFT": "IMAGING",
"US LOWER EXTREMITY ARTERIES ISCHEMIC LEVEL 1 RIGHT": "IMAGING",
"US LOWER EXTREMITY JOINT COMPLETE LEFT": "IMAGING",
"US LOWER EXTREMITY JOINT COMPLETE RT": "IMAGING",
"US LOWER EXTREMITY JOINT LIMITED LEFT": "IMAGING",
"US LOWER EXTREMITY JOINT LIMITED RIGHT": "IMAGING",
"US LOWER EXTREMITY VENOUS DUPLEX BILATERAL": "IMAGING",
"US LOWER EXTREMITY VENOUS DUPLEX LEFT": "IMAGING",
"US LOWER EXTREMITY VENOUS DUPLEX RIGHT": "IMAGING",
"US NECK LYMPH NODE MAPPING": "IMAGING",
"US NON-OB TRANSVAGINAL": "IMAGING",
"US OB 1ST TRI < 14 WKS": "IMAGING",
"US OB 2ND/3RD TRI >14WKS": "IMAGING",
"US OB < 14 WEEKS SINGLE OR FIRST GESTATION": "IMAGING",
"US OB < 14 WKS": "IMAGING",
"US OB < 14 WKS 1 FETUS": "IMAGING",
"US OB < 14 WKS 2 FETUS": "IMAGING",
"US OB < 14 WKS 3 FETUS": "IMAGING",
"US OB < 14 WKS 4 FETUS": "IMAGING",
"US OB < 14 WKS AND US OB TRANSVAGINAL": "IMAGING",
"US OB < 14 WKS AND US OB TRANSVAGINAL 3 FETUS": "IMAGING",
"US OB < 14 WKS AND US OB TRANSVAGINAL 4 FETUS": "IMAGING",
"US OB < 14 WKS AND US TRANSVAGINAL 2 FETUS": "IMAGING",
"US OB <14 WKS SINGLE TRANSABD IN OB DEPT": "IMAGING",
"US OB <14WKS EACH ADD TRANSABD IN OB DEPT": "IMAGING",
"US OB > 14 WEEKS": "IMAGING",
"US OB > 14 WEEKS 1 FETUS": "IMAGING",
"US OB > 14 WEEKS 2 FETUS": "IMAGING",
"US OB > 14 WEEKS 2ND-3RD TRIMESTER": "IMAGING",
"US OB > 14 WEEKS 3 FETUS": "IMAGING",
"US OB > 14 WEEKS 4 FETUS": "IMAGING",
"US OB > 14 WEEKS AND US OB TRANSVAGINAL": "IMAGING",
"US OB > 14 WEEKS AND US OB TRANSVAGINAL 1 FETUS": "IMAGING",
"US OB > 14 WEEKS AND US OB TRANSVAGINAL 2 FETUS": "IMAGING",
"US OB > 14 WEEKS AND US OB TRANSVAGINAL 3 FETUS": "IMAGING",
"US OB > 14 WEEKS AND US ON TRANSVAGINAL 4 FETUS": "IMAGING",
"US OB >14WKS EACH ADD TRANSABD IN OB DEPT": "IMAGING",
"US OB >14WKS SINGLE TRANSABD IN OB DEPT": "IMAGING",
"US OB BIOPHYSICAL PROFILE W/STRS IN OB DEPT": "IMAGING",
"US OB BIOPHYSICAL PROFILE WO STR IN OB DEPT": "IMAGING",
"US OB FETAL NUCHAL TRANS <14WKS": "IMAGING",
"US OB FETAL NUCHAL TRANS <14WKS MULT": "IMAGING",
"US OB FETAL NUCHAL TRANSLUCENCY 1ST TRIMESTER": "IMAGING",
"US OB FETAL NUCHAL TRANSLUCENCY 1ST TRIMESTER 1 FETUS": "IMAGING",
"US OB FETAL NUCHAL TRANSLUCENCY 1ST TRIMESTER 2 FETUS": "IMAGING",
"US OB FETAL NUCHAL TRANSLUCENCY 1ST TRIMESTER 3 FETUS": "IMAGING",
"US OB FETAL NUCHAL TRANSLUCENCY 1ST TRIMESTER 4 FETUS": "IMAGING",
"US OB FU OR REPEAT IN OB DEPT": "IMAGING",
"US OB LIMITED DONE IN OB DEPT": "IMAGING",
"US OB MUL 1ST TRI< 14WKS EA AD": "IMAGING",
"US OB TRANSVAG AND US OB W FETAL ANATOMIC EVAL 1 FETUS": "IMAGING",
"US OB TRANSVAG AND US OB W FETAL ANATOMIC EVAL 2 FETUS": "IMAGING",
"US OB TRANSVAG AND US OB W FETAL ANATOMIC EVAL 3 FETUS": "IMAGING",
"US OB TRANSVAG AND US OB W FETAL ANATOMIC EVAL 4 FETUS": "IMAGING",
"US OB TRANSVAG DONE IN OB DEPT": "IMAGING",
"US OB TRANSVAGINAL": "IMAGING",
"US OB W FETAL ANATOMIC EVAL": "IMAGING",
"US OB W FETAL ANATOMIC EVAL 1 FETUS": "IMAGING",
"US OB W FETAL ANATOMIC EVAL 2 FETUS": "IMAGING",
"US OB W FETAL ANATOMIC EVAL 3 FETUS": "IMAGING",
"US OB W FETAL ANATOMIC EVAL 4 FETUS": "IMAGING",
"US OB< 14 WKS AND US TRANSVAGINAL 1 FETUS": "IMAGING",
"US PANCREAS": "IMAGING",
"US PANCREAS TRANSPLANT": "IMAGING",
"US PANCREAS TRANSPLANT COMPLETE": "IMAGING",
"US PANCREAS TRANSPLANT LIMITED": "IMAGING",
"US PARATHYROID": "IMAGING",
"US PELVIS COMP NON-OB TRANSABDOMINAL": "IMAGING",
"US PELVIS COMP NON-OB TRANSABDOMINAL AND TRANSVAG": "IMAGING",
"US PELVIS COMP NON-OB TRANSVAGINAL": "IMAGING",
"US PELVIS COMPLETE DONE IN OB DEPT": "IMAGING",
"US PELVIS COMPLETE NON OB": "IMAGING",
"US PELVIS FETAL FOLLOW UP": "IMAGING",
"US PELVIS LIMITED": "IMAGING",
"US PELVIS LIMITED DONE IN OB": "IMAGING",
"US PELVIS NON OB AND DUPLEX COMPLETE": "IMAGING",
"US PELVIS NON OB TRANSABDOMINAL AND DUPLEX COMPLETE": "IMAGING",
"US PELVIS NON OB TRANSVAGINAL AND DUPLEX COMPLETE": "IMAGING",
"US PELVIS NON-OB TRANSABD AND TRANSVAG AND DUPLEX COMPLETE": "IMAGING",
"US PELVIS OB EVAL LIMITED": "IMAGING",
"US PELVIS OB W FETAL ANAT EVAL EA ADDL GESTATION": "IMAGING",
"US PELVIS OB W FETAL ANATOMIC EVAL": "IMAGING",
"US PELVIS TRANSVAG DONE IN OB DEPT": "IMAGING",
"US PELVIS TRANSVAGINAL": "IMAGING",
"US PELVIS W/O TRANSVAGINA": "IMAGING",
"US PENIS DOPPLER COMPLETE": "IMAGING",
"US PLACENTAL LOCATION": "IMAGING",
"US PROC UNLISTED": "IMAGING",
"US PROSTATE VOLUME STUDY": "IMAGING",
"US PROSTATE W BIOPSY": "IMAGING",
"US PROSTATE W BIOPSY W FUSION": "IMAGING",
"US PROSTATE WITH GOLD SEED IMPLANT": "IMAGING",
"US PYLORIS": "IMAGING",
"US RAD REVIEW 2ND OPINION": "IMAGING",
"US RADIO TX CATHETER PLACEMENT": "IMAGING",
"US RADIOLOGIST REVIEW OF OUTSIDE IMAGES": "IMAGING",
"US RAYNAUDS EVALUATION": "IMAGING",
"US RENAL AND DOPPLER BILATERAL": "IMAGING",
"US RENAL AND DOPPLER LEFT": "IMAGING",
"US RENAL AND DOPPLER RIGHT": "IMAGING",
"US RENAL COMPLETE": "IMAGING",
"US RENAL COMPLETE (COMPLETE URINARY SYSTEM)": "IMAGING",
"US RENAL DOPPLER ONLY BILATERAL": "IMAGING",
"US RENAL DOPPLER ONLY LEFT": "IMAGING",
"US RENAL DOPPLER ONLY RIGHT": "IMAGING",
"US RENAL ONLY BILATERAL": "IMAGING",
"US RENAL ONLY LEFT": "IMAGING",
"US RENAL ONLY RIGHT": "IMAGING",
"US RENAL TRANSPLANT": "IMAGING",
"US RENAL TRANSPLANT BILAT": "IMAGING",
"US RENAL TRANSPLANT LT": "IMAGING",
"US RENAL TRANSPLANT RT": "IMAGING",
"US RETROPERITONEAL COMPLETE": "IMAGING",
"US RETROPERITONEAL LIMITED": "IMAGING",
"US SALINE SONOHYSTEROGRAM": "IMAGING",
"US SOFT TISSUE ABDOMINAL WALL": "IMAGING",
"US SOFT TISSUE AXILLA BILATERAL": "IMAGING",
"US SOFT TISSUE AXILLA LEFT": "IMAGING",
"US SOFT TISSUE AXILLA RIGHT": "IMAGING",
"US SOFT TISSUE BUTTOCKS": "IMAGING",
"US SOFT TISSUE CHEST WALL": "IMAGING",
"US SOFT TISSUE HEAD/NECK": "IMAGING",
"US SOFT TISSUE LOWER BACK": "IMAGING",
"US SOFT TISSUE LOWER EXTREMITY BILATERAL": "IMAGING",
"US SOFT TISSUE LOWER EXTREMITY LEFT": "IMAGING",
"US SOFT TISSUE LOWER EXTREMITY RIGHT": "IMAGING",
"US SOFT TISSUE NECK OR HEAD": "IMAGING",
"US SOFT TISSUE PELVIC WALL": "IMAGING",
"US SOFT TISSUE PENIS": "IMAGING",
"US SOFT TISSUE PERINEUM": "IMAGING",
"US SOFT TISSUE UPPER BACK": "IMAGING",
"US SOFT TISSUE UPPER EXTREMITY BILATERAL": "IMAGING",
"US SOFT TISSUE UPPER EXTREMITY LEFT": "IMAGING",
"US SOFT TISSUE UPPER EXTREMITY RIGHT": "IMAGING",
"US SONOHYSTEROGRAM SALINE": "IMAGING",
"US SONOHYSTOGRAM DOPPLER": "IMAGING",
"US SPINAL CANAL AND CONTENTS": "IMAGING",
"US SPLEEN": "IMAGING",
"US SPLEEN W DOPPLER COMPLETE": "IMAGING",
"US SPLEEN W DOPPLER LIMITED": "IMAGING",
"US SPLEEN WO DOPPLER": "IMAGING",
"US TESTICLE AND SCROTUM LEFT": "IMAGING",
"US TESTICLE AND SCROTUM RIGHT": "IMAGING",
"US TESTICLE AND SCROTUM W DOPPLER LEFT": "IMAGING",
"US TESTICLE AND SCROTUM W DOPPLER RIGHT": "IMAGING",
"US TESTICLES AND SCROTUM BILATERAL": "IMAGING",
"US TESTICLES AND SCROTUM W DOPPLER BILATERAL": "IMAGING",
"US THORACIC OUTLET STUDY": "IMAGING",
"US THYROID ONLY": "IMAGING",
"US TRANSCRANIAL DOPPLER": "IMAGING",
"US TRANSRECTAL": "IMAGING",
"US ULTRA CLIP TISS MARK FOR BX": "IMAGING",
"US ULTRA CLIP TISSUE MARKER FOR BX": "IMAGING",
"US UMBILICAL VEIN DOPPLER": "IMAGING",
"US UNLISTED": "IMAGING",
"US UNLISTED PROCEDURE": "IMAGING",
"US UPPER EXTREMITY ABI MULTIPLE LEVELS NO STRESS": "IMAGING",
"US UPPER EXTREMITY ARTERIES DUPLEX BILATERAL": "IMAGING",
"US UPPER EXTREMITY ARTERIES DUPLEX LEFT": "IMAGING",
"US UPPER EXTREMITY ARTERIES DUPLEX RIGHT": "IMAGING",
"US UPPER EXTREMITY ARTERIES ISCHEMIC LEVEL 1 BILATERAL": "IMAGING",
"US UPPER EXTREMITY ARTERIES ISCHEMIC LEVEL 1 LEFT": "IMAGING",
"US UPPER EXTREMITY ARTERIES ISCHEMIC LEVEL 1 RIGHT": "IMAGING",
"US UPPER EXTREMITY JOINT COMPLETE LEFT": "IMAGING",
"US UPPER EXTREMITY JOINT COMPLETE RIGHT": "IMAGING",
"US UPPER EXTREMITY JOINT LIMITED LEFT": "IMAGING",
"US UPPER EXTREMITY JOINT LIMITED RIGHT": "IMAGING",
"US UPPER EXTREMITY VENOUS DUPLEX BILATERAL": "IMAGING",
"US UPPER EXTREMITY VENOUS DUPLEX LEFT": "IMAGING",
"US UPPER EXTREMITY VENOUS DUPLEX RIGHT": "IMAGING",
"US URINARY BLADDER": "IMAGING",
"US VENOUS NON INVASIVE PHYSIOLOGIC EXTREM STUDY BILATERAL": "IMAGING",
"US VESSEL MAPPING DIALYSIS ACCESS PRE OP BILATERAL": "IMAGING",
"US VESSEL MAPPING DIALYSIS ACCESS PRE OP LEFT": "IMAGING",
"US VESSEL MAPPING DIALYSIS ACCESS PRE OP RIGHT": "IMAGING",
"US VESSEL MAPPING DIALYSYS ACCESS (PRE OP)": "IMAGING",
"US-GUIDE NEEDLE BIOPS": "IMAGING",
"VASCULAR BIOPSY": "IMAGING",
"VASCULAR STUDY NON CARDIAC": "IMAGING",
"VEN THROMBOSIS IMAGES, BILAT": "IMAGING",
"VENOGRAM ADRENAL BILAT": "IMAGING",
"VENOGRAM ADRENAL UNILAT": "IMAGING",
"VENOGRAM EPIDURAL": "IMAGING",
"VENOGRAM HEPATIC": "IMAGING",
"VENOGRAM HEPATIC W HEMODYNAMICS": "IMAGING",
"VENOGRAM LEG BILAT": "IMAGING",
"VENOGRAM ORBITAL": "IMAGING",
"VENOGRAM RENAL BILAT": "IMAGING",
"VENOGRAM RENAL UNILAT": "IMAGING",
"VENOGRAM SPLENOPORTOGRAM": "IMAGING",
"VENOGRAM SUPER SAG SINUS": "IMAGING",
"VENOGRAM UNILAT OFF PREMISE CHARGE ONLY": "IMAGING",
"VENOUS SAMPLING BY CATHETER": "IMAGING",
"VENOUS THROMBOSIS IMAGING": "IMAGING",
"VENOUS THROMBOSIS STUDY": "IMAGING",
"VENT IMAGE, 1 BREATH, 1 PROJ": "IMAGING",
"VENT IMAGE, 1 PROJ, GAS": "IMAGING",
"VENT IMAGE, MULT PROJ, GAS": "IMAGING",
"VERTEBRAL FRACTURE ASSESSMENT": "IMAGING",
"VERTEBRAL FX ASSESSMENT VIA DUAL ENERGY XRAY ABSORPT ": "IMAGING",
"VESSEL MAPPING VESSELS HEMODIALYSIS ACCESS": "IMAGING",
"VISUAL EVOKED POTENTIAL": "IMAGING",
"VIT B-12 ABSORP EXAM NO IF": "IMAGING",
"VIT B-12 ABSORP EXAM, IF": "IMAGING",
"VIT B-12 ABSORP, COMBINED": "IMAGING",
"WADA ACTIVATION TEST": "IMAGING",
"WALL MOTION & EJECTION FRACTION W/MYOCARDIAL BLOOD FLOW ": "IMAGING",
"WALL MOTION AND EJECTION FRACTION": "IMAGING",
"WEEKLY RADN RX COMPLEX": "IMAGING",
"WEEKLY RADN RX CONFORMAL": "IMAGING",
"WEEKLY RADN RX INTERMED": "IMAGING",
"WEEKLY RADN RX SIMPLE": "IMAGING",
"X-RAY ABDOMEN 1+ VW": "IMAGING",
"X-RAY ABDOMEN 2 VW": "IMAGING",
"X-RAY ABDOMEN KUB": "IMAGING",
"X-RAY ABDOMEN SERIES W/PA CHES": "IMAGING",
"X-RAY AC JTS BILATERAL": "IMAGING",
"X-RAY ANKLE 2 VW": "IMAGING",
"X-RAY ANKLE 3+ VW": "IMAGING",
"X-RAY B.E. REDUCTN INTUSS": "IMAGING",
"X-RAY CERV SPINE 7VW+FLEX & EX": "IMAGING",
"X-RAY CERVICAL SPINE 4-5 VIEWS": "IMAGING",
"X-RAY CHEST 1 VW": "IMAGING",
"X-RAY CHEST 2 VW": "IMAGING",
"X-RAY CHEST 4 VW": "IMAGING",
"X-RAY CHEST 4 VW + FLUORO": "IMAGING",
"X-RAY CHEST PA & LATERAL W OBLIQUES": "IMAGING",
"X-RAY CHEST W APICAL LORD": "IMAGING",
"X-RAY CHEST W FLUORO": "IMAGING",
"X-RAY CHOLECYSTGRAM/FATTY MEAL": "IMAGING",
"X-RAY CHOLECYSTOGRAM(ORAL)": "IMAGING",
"X-RAY CLAVICLE": "IMAGING",
"X-RAY COLON AIR CONTRAST": "IMAGING",
"X-RAY COLON CONTRAST BARIUM ENEMA": "IMAGING",
"X-RAY CYSTOGRAM": "IMAGING",
"X-RAY DIGIT(S) TOES": "IMAGING",
"X-RAY ELBOW 2 VW": "IMAGING",
"X-RAY ELBOW 3+ VW": "IMAGING",
"X-RAY EXAM SELLA": "IMAGING",
"X-RAY EXAM, SACROILIAC JOINT": "IMAGING",
"X-RAY FACIAL BONES 3 + VW": "IMAGING",
"X-RAY FACIAL BONES <3 VW": "IMAGING",
"X-RAY FISTULA/ABSCESS SINUS TRACT": "IMAGING",
"X-RAY FOOT 2 VW": "IMAGING",
"X-RAY FOOT 3+ VW": "IMAGING",
"X-RAY FOR BONE AGE": "IMAGING",
"X-RAY GUIDANCE FOR BIOPSY": "IMAGING",
"X-RAY GUIDE ENTEROCLYSIS TUBE": "IMAGING",
"X-RAY HEAD FOR ORTHODONTIA": "IMAGING",
"X-RAY HEEL 1 VW BILAT": "IMAGING",
"X-RAY HEEL 1 VW LEFT": "IMAGING",
"X-RAY HEEL 1 VW RIGHT": "IMAGING",
"X-RAY HEEL 2 VW BILAT": "IMAGING",
"X-RAY HEEL 2 VW LEFT": "IMAGING",
"X-RAY HEEL 2 VW RIGHT": "IMAGING",
"X-RAY HEEL(OS CALCIS)": "IMAGING",
"X-RAY HIP OPERATV": "IMAGING",
"X-RAY HIPS 4 VW BILAT + PELVIS": "IMAGING",
"X-RAY HUMERUS 2 VW": "IMAGING",
"X-RAY HYPOTONIC DUODENOGRAPHY": "IMAGING",
"X-RAY HYSTEROSALPINGOGRAM": "IMAGING",
"X-RAY INTRODUCTN GI TUBE": "IMAGING",
"X-RAY IV PYELOGRAM (IVP)": "IMAGING",
"X-RAY IV PYELOGRAM AND TOMOGRAPHY": "IMAGING",
"X-RAY IV PYELOGRAM DRIP INFUSION": "IMAGING",
"X-RAY IV PYELOGRAM HYPERTENSV": "IMAGING",
"X-RAY LEG, INFANT 2 VW": "IMAGING",
"X-RAY LOWER LEG(TIB/FIB)": "IMAGING",
"X-RAY LUMBAR SP OBLIQUES ONLY": "IMAGING",
"X-RAY LUMBAR SPINE FLEX/EXTEN": "IMAGING",
"X-RAY LUMBOSACRAL": "IMAGING",
"X-RAY MANDIBLE 4 + VW": "IMAGING",
"X-RAY MANDIBLE <4VW": "IMAGING",
"X-RAY MASTOIDS 3 + VW": "IMAGING",
"X-RAY MASTOIDS <3 VW": "IMAGING",
"X-RAY MIDDLE EAR": "IMAGING",
"X-RAY NASAL BONES": "IMAGING",
"X-RAY NECK SOFT TISSUE": "IMAGING",
"X-RAY NEPHROSTOGRAM LOOPOGRAM": "IMAGING",
"X-RAY NOSE-RECTUM CHILD F.B.": "IMAGING",
"X-RAY OF MAMMARY DUCT": "IMAGING",
"X-RAY OF MAMMARY DUCTS": "IMAGING",
"X-RAY OPER CHOLANGIO ADDNL SET": "IMAGING",
"X-RAY OPTIC FORAMEN": "IMAGING",
"X-RAY ORBITS": "IMAGING",
"X-RAY ORBITS FOR FOREIGN BODY": "IMAGING",
"X-RAY PELVIMETRY": "IMAGING",
"X-RAY PELVIS 1 VW": "IMAGING",
"X-RAY PELVIS 3 + VW": "IMAGING",
"X-RAY PELVIS/HIPS CHILD/INFANT": "IMAGING",
"X-RAY PENIS": "IMAGING",
"X-RAY PERCUT GASTROSTOMY TUBE": "IMAGING",
"X-RAY PERCUT XHEPATIC CHOLANGIO": "IMAGING",
"X-RAY PERINEOGRAM": "IMAGING",
"X-RAY PERITONEUM": "IMAGING",
"X-RAY POSTOP BILE STONE REMOVAL": "IMAGING",
"X-RAY RENAL CYST XLUMBAR+CONTRST": "IMAGING",
"X-RAY RETROGRADE PYELOGRAM": "IMAGING",
"X-RAY RIBS 2 VW UNILAT": "IMAGING",
"X-RAY RIBS, BILAT W/PA CHEST": "IMAGING",
"X-RAY SACROILIAC JTS 3 + VW": "IMAGING",
"X-RAY SACROILIAC JTS <3 VW": "IMAGING",
"X-RAY SACRUM,COCCYX 2 + VW": "IMAGING",
"X-RAY SALIVARY GLAND": "IMAGING",
"X-RAY SCAPULA": "IMAGING",
"X-RAY SCOLIOSIS SUPINE & ERECT": "IMAGING",
"X-RAY SHOULDER 1 VW": "IMAGING",
"X-RAY SHOULDER COMPLETE": "IMAGING",
"X-RAY SIALOGRAM LEFT": "IMAGING",
"X-RAY SINUSES 2 VW": "IMAGING",
"X-RAY SINUSES 3 + VW": "IMAGING",
"X-RAY SKULL 4 + VW": "IMAGING",
"X-RAY SKULL <4 VW": "IMAGING",
"X-RAY SMALL BOWEL ENTEROCLYSIS": "IMAGING",
"X-RAY SMALL BOWELL": "IMAGING",
"X-RAY SPINE SURVEY": "IMAGING",
"X-RAY STERNOCLAVICULAR JT 3+VW": "IMAGING",
"X-RAY STERNUM 2 + VW": "IMAGING",
"X-RAY T-TUBE CHOLANGIOGRAM": "IMAGING",
"X-RAY TEETH PARTIAL": "IMAGING",
"X-RAY TEETH SINGLE": "IMAGING",
"X-RAY THORACIC SPINE 2 VW": "IMAGING",
"X-RAY THORACIC SPINE W/OBLIQUE": "IMAGING",
"X-RAY THROAT/CERV ESOPHA CONTRHA": "IMAGING",
"X-RAY TMJ BILAT": "IMAGING",
"X-RAY UPPER GI AIR CONT + KUB": "IMAGING",
"X-RAY UPPER GI AIR CONT + SBS": "IMAGING",
"X-RAY UPPER GI AIR CONTRAST": "IMAGING",
"X-RAY UPPER GI SM BOWEL": "IMAGING",
"X-RAY UPPER GI TRACT + KUB": "IMAGING",
"X-RAY UPPER GI W/O KUB": "IMAGING",
"X-RAY URETHROCYSTOGRAM": "IMAGING",
"X-RAY URETHROCYSTOGRAM/VOIDING": "IMAGING",
"X-RAY VESICULOGM MALE GENL TRCT": "IMAGING",
"X-RAY XCERV CATH FALLOPIAN TUBE": "IMAGING",
"X-RAY XERORADIOGRAM": "IMAGING",
"X-RAY, BILE DUCT DILATION": "IMAGING",
"X-RAYS, BONE SURVEY LIMITED": "IMAGING",
"X-RAYS,BONE SURVEY INFANT": "IMAGING",
"XENON XE-133 GAS, DIAGNOSTIC, PER 10 MILLICURIES": "IMAGING",
"XR ABDOMEN 1 VW DECUB LEFT": "IMAGING",
"XR ABDOMEN 1 VW DECUB RIGHT": "IMAGING",
"XR ABDOMEN 1 VW KUB SUPINE": "IMAGING",
"XR ABDOMEN 1 VW UPRIGHT": "IMAGING",
"XR ABDOMEN 2 VW": "IMAGING",
"XR ABDOMEN AP OBLIQUE W CONE VIEWS": "IMAGING",
"XR ABDOMEN SERIES": "IMAGING",
"XR AC JOINT BILATERAL": "IMAGING",
"XR AC JOINT LEFT": "IMAGING",
"XR AC JOINT RIGHT": "IMAGING",
"XR ANKLE 1 VW STANDING BILATERAL": "IMAGING",
"XR ANKLE 1 VW STANDING LEFT": "IMAGING",
"XR ANKLE 1 VW STANDING RIGHT": "IMAGING",
"XR ANKLE 2 VW STANDING BILATERAL": "IMAGING",
"XR ANKLE 2 VW STANDING LEFT": "IMAGING",
"XR ANKLE 2 VW STANDING RIGHT": "IMAGING",
"XR ANKLE 1 VW BILATERAL": "IMAGING",
"XR ANKLE 1 VW LEFT": "IMAGING",
"XR ANKLE 1 VW RIGHT": "IMAGING",
"XR ANKLE 2 VW BILATERAL": "IMAGING",
"XR ANKLE 2 VW LEFT": "IMAGING",
"XR ANKLE 2 VW RIGHT": "IMAGING",
"XR ANKLE 3 VW INCL STANDING BILATERAL": "IMAGING",
"XR ANKLE 3 VW INCL STANDING LEFT": "IMAGING",
"XR ANKLE 3 VW INCL STANDING RIGHT": "IMAGING",
"XR ANKLE 3+ VW BILATERAL": "IMAGING",
"XR ANKLE 3+ VW LEFT": "IMAGING",
"XR ANKLE 3+ VW RIGHT": "IMAGING",
"XR ARTHROGRAM HIP": "IMAGING",
"XR BONE AGE HAND AND WRIST": "IMAGING",
"XR BONE LENGTH EVALUATION": "IMAGING",
"XR BONE SURVEY COMPLETE": "IMAGING",
"XR BONE SURVEY COMPLETE > 12 MONTHS": "IMAGING",
"XR BONE SURVEY INFANT OR CHILD": "IMAGING",
"XR BRONCHOGRAM BILATERAL": "IMAGING",
"XR BRONCHOGRAM LEFT": "IMAGING",
"XR BRONCHOGRAM RIGHT": "IMAGING",
"XR CERV SPINE 7VW+FLEX AND EXT": "IMAGING",
"XR CERVICAL SPINE 1 VW": "IMAGING",
"XR CERVICAL SPINE 2-3 VW": "IMAGING",
"XR CERVICAL SPINE 4-5 VIEWS": "IMAGING",
"XR CERVICAL SPINE FLEX AND EXT ONLY": "IMAGING",
"XR CHEST 4 + VW": "IMAGING",
"XR CHEST AP OR PA": "IMAGING",
"XR CHEST APICAL LORDOTIC VW": "IMAGING",
"XR CHEST LATERAL DECUBITUS LEFT": "IMAGING",
"XR CHEST LATERAL DECUBITUS RIGHT": "IMAGING",
"XR CHEST LATERAL VIEW ONLY": "IMAGING",
"XR CHEST OBLIQUE VIEWS ONLY": "IMAGING",
"XR CHEST PA AND LAT W OBLIQUES": "IMAGING",
"XR CHEST PA AND LATERAL": "IMAGING",
"XR CHEST PA AND LATERAL W OBL": "IMAGING",
"XR CHEST PA EXPIRATION": "IMAGING",
"XR CHEST PA LATERAL AND APICAL LORDOTIC": "IMAGING",
"XR CHEST PA WITH OBLIQUE VIEWS": "IMAGING",
"XR CHEST/ABDOMEN INFANT 1 VIEW AP": "IMAGING",
"XR CHEST/ABDOMEN INFANT 2 VIEW AP/LAT": "IMAGING",
"XR CHEST/ABDOMEN INFANT CROSS TABLE LATERAL": "IMAGING",
"XR CLAVICLE BILATERAL": "IMAGING",
"XR CLAVICLE LEFT": "IMAGING",
"XR CLAVICLE RIGHT": "IMAGING",
"XR ELBOW 1 VW BILATERAL": "IMAGING",
"XR ELBOW 1 VW LEFT": "IMAGING",
"XR ELBOW 1 VW RIGHT": "IMAGING",
"XR ELBOW 2 VW BILATERAL": "IMAGING",
"XR ELBOW 2 VW LEFT": "IMAGING",
"XR ELBOW 2 VW RIGHT": "IMAGING",
"XR ELBOW 3+ VW BILATERAL": "IMAGING",
"XR ELBOW 3+ VW LEFT": "IMAGING",
"XR ELBOW 3+ VW RIGHT": "IMAGING",
"XR ELBOW 4 VW BILATERAL": "IMAGING",
"XR ELBOW 4 VW LEFT": "IMAGING",
"XR ELBOW 4 VW RIGHT": "IMAGING",
"XR EYE FOREIGN BODY": "IMAGING",
"XR FACIAL BONES 3 + VW": "IMAGING",
"XR FACIAL BONES < 3 VW": "IMAGING",
"XR FEMUR 1 VW BILATERAL": "IMAGING",
"XR FEMUR 1 VW LEFT": "IMAGING",
"XR FEMUR 1 VW RIGHT": "IMAGING",
"XR FEMUR 2+ VW BILATERAL": "IMAGING",
"XR FEMUR 2+ VW LEFT": "IMAGING",
"XR FEMUR 2+ VW RIGHT": "IMAGING",
"XR FINGER 1 VW BILATERAL": "IMAGING",
"XR FINGER 1 VW LEFT": "IMAGING",
"XR FINGER 1 VW RIGHT": "IMAGING",
"XR FINGER 1 VW RIGHT ": "IMAGING",
"XR FINGER MIN 2 VW BILATERAL": "IMAGING",
"XR FINGER MIN 2 VW LEFT": "IMAGING",
"XR FINGER MIN 2 VW RIGHT": "IMAGING",
"XR FOOT 1 VW BILATERAL": "IMAGING",
"XR FOOT 1 VW LEFT": "IMAGING",
"XR FOOT 1 VW RIGHT": "IMAGING",
"XR FOOT 2 VW BILATERAL": "IMAGING",
"XR FOOT 2 VW LEFT": "IMAGING",
"XR FOOT 2 VW RIGHT": "IMAGING",
"XR FOOT 2 VW STANDING BILATERAL": "IMAGING",
"XR FOOT 2 VW STANDING LEFT": "IMAGING",
"XR FOOT 2 VW STANDING RIGHT": "IMAGING",
"XR FOOT 3+ VW BILATERAL": "IMAGING",
"XR FOOT 3+ VW LEFT": "IMAGING",
"XR FOOT 3+ VW RIGHT": "IMAGING",
"XR FOOT 3+ VW STANDING BILATERAL": "IMAGING",
"XR FOOT 3+ VW STANDING LEFT": "IMAGING",
"XR FOOT 3+ VW STANDING RIGHT": "IMAGING",
"XR FOOT LATERAL STANDING BILATERAL": "IMAGING",
"XR FOOT LATERAL STANDING LEFT": "IMAGING",
"XR FOOT LATERAL STANDING RIGHT": "IMAGING",
"XR FOR BONE AGE": "IMAGING",
"XR FOREARM 2 VW BILATERAL": "IMAGING",
"XR FOREARM 2 VW LEFT": "IMAGING",
"XR FOREARM 2 VW RIGHT": "IMAGING",
"XR HAND 1 VW BILATERAL": "IMAGING",
"XR HAND 1 VW LEFT": "IMAGING",
"XR HAND 1 VW RIGHT": "IMAGING",
"XR HAND 2 VIEW BILATERAL": "IMAGING",
"XR HAND 2 VIEW LEFT": "IMAGING",
"XR HAND 2 VIEW RIGHT": "IMAGING",
"XR HAND 3+ VIEW BILATERAL": "IMAGING",
"XR HAND 3+ VIEW LEFT": "IMAGING",
"XR HAND 3+ VIEW RIGHT": "IMAGING",
"XR HEAD FOR ORTHODONTIA": "IMAGING",
"XR HEEL CALCANEUS 1 VW BILATERAL": "IMAGING",
"XR HEEL CALCANEUS 1 VW LEFT": "IMAGING",
"XR HEEL CALCANEUS 1 VW RIGHT": "IMAGING",
"XR HEEL CALCANEUS 2+ VW BILATERAL": "IMAGING",
"XR HEEL CALCANEUS 2+ VW LEFT": "IMAGING",
"XR HEEL CALCANEUS 2+ VW RIGHT": "IMAGING",
"XR HEEL CALCANEUS STANDING 1 VW BILATERAL": "IMAGING",
"XR HEEL CALCANEUS STANDING 1 VW LEFT": "IMAGING",
"XR HEEL CALCANEUS STANDING 1 VW RIGHT": "IMAGING",
"XR HIP 1 VIEW BILATERAL AND PELVIS": "IMAGING",
"XR HIP 1 VIEW LEFT AND PELVIS": "IMAGING",
"XR HIP 1 VIEW RIGHT AND PELVIS": "IMAGING",
"XR HIP 1 VW BILATERAL": "IMAGING",
"XR HIP 1 VW LEFT": "IMAGING",
"XR HIP 1 VW RIGHT": "IMAGING",
"XR HIP 2 VIEW BILATERAL AND PELVIS": "IMAGING",
"XR HIP 2 VW BILATERAL": "IMAGING",
"XR HIP 2 VW LEFT": "IMAGING",
"XR HIP 2 VW RIGHT": "IMAGING",
"XR HIP 2-3 VIEW LEFT AND PELVIS": "IMAGING",
"XR HIP 2-3 VIEW RIGHT AND PELVIS": "IMAGING",
"XR HIP 3 VW BILATERAL": "IMAGING",
"XR HIP 3 VW LEFT": "IMAGING",
"XR HIP 3 VW RIGHT": "IMAGING",
"XR HIP 3-4 VIEW BILATERAL AND PELVIS": "IMAGING",
"XR HIP 4+ VIEW LEFT AND PELVIS": "IMAGING",
"XR HIP 4+ VW RIGHT AND PELVIS": "IMAGING",
"XR HIP 5+ VIEW BILATERAL AND PELVIS": "IMAGING",
"XR HIP IN SURGERY": "IMAGING",
"XR HIP IN SURGERY SINGLE VW-1 IMAGE": "IMAGING",
"XR HIP IN SURGERY SINGLE VW-2 IMAGES": "IMAGING",
"XR HIP IN SURGERY SINGLE VW-3 IMAGES": "IMAGING",
"XR HIP IN SURGERY SINGLE VW-4 OR MORE IMAGES": "IMAGING",
"XR HIP INTEROPERATIVE BILATERAL": "IMAGING",
"XR HIP INTRAOPERATIVE LEFT": "IMAGING",
"XR HIP INTRAOPERATIVE RIGHT": "IMAGING",
"XR HIPS BILATERAL 2+ VW W AP PELVIS": "IMAGING",
"XR HUMERUS 1 VW BILATERAL": "IMAGING",
"XR HUMERUS 1 VW LEFT": "IMAGING",
"XR HUMERUS 1 VW RIGHT": "IMAGING",
"XR HUMERUS 2 VW BILATERAL": "IMAGING",
"XR HUMERUS 2 VW LEFT": "IMAGING",
"XR HUMERUS 2 VW RIGHT": "IMAGING",
"XR HUMERUS TRAN THORACIC VW BILATERAL": "IMAGING",
"XR HUMERUS TRAN THORACIC VW LEFT": "IMAGING",
"XR HUMERUS TRAN THORACIC VW RIGHT": "IMAGING",
"XR HYPERBARIC BONE SURVEY": "IMAGING",
"XR JOINT SURVEY AP 2 + JOINTS": "IMAGING",
"XR KNEE 1 OR 2 VW BILATERAL": "IMAGING",
"XR KNEE 1 OR 2 VW LEFT": "IMAGING",
"XR KNEE 1 OR 2 VW RIGHT": "IMAGING",
"XR KNEE 1 VW BILATERAL AND AP STANDING KNEE BILATERAL": "IMAGING",
"XR KNEE 1 VW LEFT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 1 VW RIGHT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 2 VW BILATERAL AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 2 VW LEFT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 2 VW RIGHT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 3 VW BILATERAL": "IMAGING",
"XR KNEE 3 VW BILATERAL AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 3 VW LEFT": "IMAGING",
"XR KNEE 3 VW LEFT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 3 VW RIGHT": "IMAGING",
"XR KNEE 3 VW RIGHT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 4 VW BILATERAL AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 4 VW LEFT AND AP STANDING KNEE": "IMAGING",
"XR KNEE 4 VW RIGHT AND AP STANDING BILATERAL": "IMAGING",
"XR KNEE 4+ VW BILATERAL": "IMAGING",
"XR KNEE 4+ VW LEFT": "IMAGING",
"XR KNEE 4+ VW RIGHT": "IMAGING",
"XR KNEE AP STANDING BILATERAL": "IMAGING",
"XR LEG LENGTH EVALUATION": "IMAGING",
"XR LOWER EXTREMITY INFANT 2+ VW BILATERAL": "IMAGING",
"XR LOWER EXTREMITY INFANT 2+ VW LEFT": "IMAGING",
"XR LOWER EXTREMITY INFANT 2+ VW RIGHT": "IMAGING",
"XR LUMBAR SPINE 1 VW": "IMAGING",
"XR LUMBAR SPINE 2 OR 3 VIEWS": "IMAGING",
"XR LUMBAR SPINE 4 + VW": "IMAGING",
"XR LUMBAR SPINE AP AND/OR LAT W BENDING VIEW": "IMAGING",
"XR LUMBAR SPINE AP LAT FLEX EXT": "IMAGING",
"XR LUMBAR SPINE AP LAT OBLIQUES FLEX AND EXT": "IMAGING",
"XR LUMBAR SPINE AP LATERAL AND OBLIQUES": "IMAGING",
"XR LUMBAR SPINE FLEX AND EXT ONLY 4 + VW": "IMAGING",
"XR LUMBAR SPINE FLEX EXT 2 OR 3 VIEWS": "IMAGING",
"XR LUMBAR SPINE FLEX/EXT": "IMAGING",
"XR LUMBAR SPINE OBLIQUES ONLY": "IMAGING",
"XR MANDIBLE 4 + VW": "IMAGING",
"XR MANDIBLE < 4 VW": "IMAGING",
"XR MASTOIDS 3 + VW": "IMAGING",
"XR MASTOIDS < 3 VW": "IMAGING",
"XR METABOLIC BONE SURVEY": "IMAGING",
"XR NASAL BONES": "IMAGING",
"XR NECK SOFT TISSUE": "IMAGING",
"XR NOSE TO RECTUM CHILD FOR FOREIGN BODY": "IMAGING",
"XR OPTIC FORAMINA": "IMAGING",
"XR ORBITS 4 + VW": "IMAGING",
"XR ORBITS <4 VWS": "IMAGING",
"XR ORTHOPANTOGRAM": "IMAGING",
"XR PACS RECORD REPORTABLE": "IMAGING",
"XR PELVIMETRY": "IMAGING",
"XR PELVIS 1 OR 2 VW": "IMAGING",
"XR PELVIS 3 VW": "IMAGING",
"XR PELVIS AND HIPS INFANT CHILD 2+ VW": "IMAGING",
"XR PELVIS IN SURGERY": "IMAGING",
"XR PELVIS IN SURGERY SINGLE VW-1 IMAGE": "IMAGING",
"XR PELVIS IN SURGERY SINGLE VW-2 IMAGES": "IMAGING",
"XR PELVIS IN SURGERY SINGLE VW-3 IMAGES": "IMAGING",
"XR PELVIS IN SURGERY SINGLE VW-4 OR MORE IMAGES": "IMAGING",
"XR RAD REVIEW 2ND OPINION": "IMAGING",
"XR RADIOLOGIST REVIEW OUTSIDE IMAGES": "IMAGING",
"XR RIBS BILATERAL 3 VW": "IMAGING",
"XR RIBS LEFT 2 VW": "IMAGING",
"XR RIBS LEFT W PA CHEST": "IMAGING",
"XR RIBS MIN 4 VIEW W PA CHEST BILATERAL": "IMAGING",
"XR RIBS RIGHT 2 VW": "IMAGING",
"XR RIBS RIGHT W PA CHEST": "IMAGING",
"XR SACROILIAC JOINTS >3 VWS": "IMAGING",
"XR SACROILIAC JTS <3 VW": "IMAGING",
"XR SACRUM AND COCCYX 2 + VW": "IMAGING",
"XR SALIVARY GLAND CALCULUS": "IMAGING",
"XR SCAPULA BILATERAL": "IMAGING",
"XR SCAPULA LEFT": "IMAGING",
"XR SCAPULA RIGHT": "IMAGING",
"XR SCOLIOSIS INCL SUPINE AND ERECT": "IMAGING",
"XR SCOLIOSIS SPINE STANDING": "IMAGING",
"XR SCOLIOSIS T&L SPINE 1 VW-CAN INCL C&S SPINE,SKULL": "IMAGING",
"XR SCOLIOSIS T&L SPINE 2-3 VW-CAN INCL C&S SPINE,SKULL": "IMAGING",
"XR SCOLIOSIS T&L SPINE 4-5 VW-CAN INCL C&S SPINE,SKULL": "IMAGING",
"XR SCOLIOSIS T&L SPINE 6 VW- CAN INCL C&S SPINE, SKULL": "IMAGING",
"XR SELLA TURCICA": "IMAGING",
"XR SHOULDER 1 VW BILATERAL": "IMAGING",
"XR SHOULDER 1 VW LEFT": "IMAGING",
"XR SHOULDER 1 VW RIGHT": "IMAGING",
"XR SHOULDER 2 VW BILATERAL": "IMAGING",
"XR SHOULDER 2 VW LEFT": "IMAGING",
"XR SHOULDER 2 VW RIGHT": "IMAGING",
"XR SHOULDER 3 VW BILATERAL": "IMAGING",
"XR SHOULDER 3 VW LEFT": "IMAGING",
"XR SHOULDER 3 VW RIGHT": "IMAGING",
"XR SHOULDER 4 VW BILATERAL": "IMAGING",
"XR SHOULDER 4 VW LEFT": "IMAGING",
"XR SHOULDER 4 VW RIGHT": "IMAGING",
"XR SHOULDER ACROMIAL ARCH BILATERAL": "IMAGING",
"XR SHOULDER ACROMIAL ARCH LEFT": "IMAGING",
"XR SHOULDER ACROMIAL ARCH RIGHT": "IMAGING",
"XR SHOULDER GRASHEY BILATERAL": "IMAGING",
"XR SHOULDER GRASHEY LEFT": "IMAGING",
"XR SHOULDER GRASHEY RIGHT": "IMAGING",
"XR SHOULDER TRANS THORACIC BILATERAL": "IMAGING",
"XR SHOULDER TRANS THORACIC LEFT": "IMAGING",
"XR SHOULDER TRANS THORACIC RIGHT": "IMAGING",
"XR SHUNT SERIES": "IMAGING",
"XR SINUSES 3 + VW": "IMAGING",
"XR SINUSES < 3 VW": "IMAGING",
"XR SITZ MARKER KUB": "IMAGING",
"XR SITZ MARKER KUB DAY 0": "IMAGING",
"XR SITZ MARKER KUB DAY 1": "IMAGING",
"XR SITZ MARKER KUB DAY 2": "IMAGING",
"XR SITZ MARKER KUB DAY 3": "IMAGING",
"XR SITZ MARKER KUB DAY 4": "IMAGING",
"XR SITZ MARKER KUB DAY 5": "IMAGING",
"XR SITZ MARKER KUB DAY 6": "IMAGING",
"XR SITZ MARKER KUB DAY 7": "IMAGING",
"XR SKULL <4 VW": "IMAGING",
"XR SKULL COMPLETE 4+ VW": "IMAGING",
"XR SPINE IN SURGERY": "IMAGING",
"XR SPINE IN SURGERY CERVICAL 2 VIEW": "IMAGING",
"XR SPINE IN SURGERY CERVICAL SINGLE VIEW-2 IMAGES": "IMAGING",
"XR SPINE IN SURGERY CERVICAL SINGLE VW-1 IMAGE": "IMAGING",
"XR SPINE IN SURGERY CERVICAL SINGLE VW-3 IMAGES": "IMAGING",
"XR SPINE IN SURGERY CERVICAL SINGLE VW-4 OR MORE IMAGES": "IMAGING",
"XR SPINE IN SURGERY LUMBAR 2 VIEW": "IMAGING",
"XR SPINE IN SURGERY LUMBAR SINGLE VIEW-1 IMAGE": "IMAGING",
"XR SPINE IN SURGERY LUMBAR SINGLE VIEW-2 IMAGES": "IMAGING",
"XR SPINE IN SURGERY LUMBAR SINGLE VIEW-3 IMAGES": "IMAGING",
"XR SPINE IN SURGERY LUMBAR SINGLE VIEW-4 OR MORE IMAGES": "IMAGING",
"XR SPINE IN SURGERY THORACIC 2 VIEW": "IMAGING",
"XR SPINE IN SURGERY THORACIC SINGLE VIEW-1 IMAGE": "IMAGING",
"XR SPINE IN SURGERY THORACIC SINGLE VIEW-2 IMAGES": "IMAGING",
"XR SPINE IN SURGERY THORACIC SINGLE VW-3 IMAGES": "IMAGING",
"XR SPINE IN SURGERY THORACIC SINGLE VW-4 OR MORE IMAGES": "IMAGING",
"XR SPINE ONE VIEW": "IMAGING",
"XR SPINE SURVEY": "IMAGING",
"XR STERNOCLAVICULAR JOINTS 3 + VW": "IMAGING",
"XR STERNUM 2 VW": "IMAGING",
"XR STRESS PERFORMED BY PHYSCIAN ANYJOINT": "IMAGING",
"XR SURGICAL SPECIMEN IMAGE-1 SPECIMEN": "IMAGING",
"XR SURGICAL SPECIMEN IMAGE-2 SPECIMENS": "IMAGING",
"XR SURGICAL SPECIMEN IMAGE-3 SPECIMENS": "IMAGING",
"XR SURGICAL SPECIMEN IMAGE-4+ SPECIMENS": "IMAGING",
"XR SURGICAL SPECIMEN IMAGING": "IMAGING",
"XR TEETH FULL MOUTH": "IMAGING",
"XR TEETH PARTIAL": "IMAGING",
"XR THORACIC SPINE 1 VW": "IMAGING",
"XR THORACIC SPINE 2 VW": "IMAGING",
"XR THORACIC SPINE 3 VW INCL SWIMMERS": "IMAGING",
"XR THORACIC SPINE AP LAT AND OBL 4 VWS": "IMAGING",
"XR THORACOLUMBAR SPINE 2 VW": "IMAGING",
"XR TIBIA FIBULA 2 VW BILATERAL": "IMAGING",
"XR TIBIA FIBULA 2 VW LEFT": "IMAGING",
"XR TIBIA FIBULA 2 VW RIGHT": "IMAGING",
"XR TMJ BILATERAL": "IMAGING",
"XR TMJ LT": "IMAGING",
"XR TMJ RT": "IMAGING",
"XR TOE 2+ VW BILATERAL": "IMAGING",
"XR TOE 2+ VW LEFT": "IMAGING",
"XR TOE 2+ VW RIGHT": "IMAGING",
"XR TOMOGRAM": "IMAGING",
"XR UNLISTED": "IMAGING",
"XR UPPER EXTREMITY INFANT 2 VW BILATERAL": "IMAGING",
"XR UPPER EXTREMITY INFANT 2 VW LEFT": "IMAGING",
"XR UPPER EXTREMITY INFANT 2 VW RIGHT": "IMAGING",
"XR WRIST 1 VIEW BILATERAL": "IMAGING",
"XR WRIST 1 VIEW LEFT": "IMAGING",
"XR WRIST 1 VIEW RIGHT": "IMAGING",
"XR WRIST 2 VW BILATERAL": "IMAGING",
"XR WRIST 2 VW LEFT": "IMAGING",
"XR WRIST 2 VW RIGHT": "IMAGING",
"XR WRIST 3+ VW BILATERAL": "IMAGING",
"XR WRIST 3+ VW LEFT": "IMAGING",
"XR WRIST 3+ VW RIGHT": "IMAGING",
"XRAY AC JTS LEFT": "IMAGING",
"XRAY AC JTS RIGHT": "IMAGING",
"XRAY ANK 3 VW INCL STAND BILAT": "IMAGING",
"XRAY ANK 3 VW INCL STANDING LT": "IMAGING",
"XRAY ANK 3 VW INCL STANDING RT": "IMAGING",
"XRAY ANKLE 1 VW BILAT": "IMAGING",
"XRAY ANKLE 1 VW LEFT": "IMAGING",
"XRAY ANKLE 1 VW RIGHT": "IMAGING",
"XRAY ANKLE 2 VW BILAT": "IMAGING",
"XRAY ANKLE 2 VW LEFT": "IMAGING",
"XRAY ANKLE 2 VW RIGHT": "IMAGING",
"XRAY ANKLE 2 VW STANDING BILAT": "IMAGING",
"XRAY ANKLE 2 VW STANDING LEFT": "IMAGING",
"XRAY ANKLE 2 VW STANDING RIGHT": "IMAGING",
"XRAY ANKLE 3+ VW BILAT": "IMAGING",
"XRAY ANKLE 3+ VW LEFT": "IMAGING",
"XRAY ANKLE 3+ VW RIGHT": "IMAGING",
"XRAY ANKLE JOINT STRESS VWS RT": "IMAGING",
"XRAY ANKLE JT STRESS VWS BILAT": "IMAGING",
"XRAY ANKLE JT STRESS VWS LEFT": "IMAGING",
"XRAY ARM, INFANT": "IMAGING",
"XRAY ARTHROGRAM ANKLE LEFT": "IMAGING",
"XRAY ARTHROGRAM ANKLE RIGHT": "IMAGING",
"XRAY ARTHROGRAM ELBOW LEFT": "IMAGING",
"XRAY ARTHROGRAM ELBOW RIGHT": "IMAGING",
"XRAY ARTHROGRAM HIP LEFT": "IMAGING",
"XRAY ARTHROGRAM HIP RIGHT": "IMAGING",
"XRAY ARTHROGRAM KNEE LEFT": "IMAGING",
"XRAY ARTHROGRAM KNEE RIGHT": "IMAGING",
"XRAY ARTHROGRAM SHOULDER LEFT": "IMAGING",
"XRAY ARTHROGRAM SHOULDER RIGHT": "IMAGING",
"XRAY ARTHROGRAM TMJ LEFT": "IMAGING",
"XRAY ARTHROGRAM TMJ RIGHT": "IMAGING",
"XRAY ARTHROGRAM WRIST LEFT": "IMAGING",
"XRAY ARTHROGRAM WRIST RIGHT": "IMAGING",
"XRAY BONE LENGTH EVALUATION": "IMAGING",
"XRAY BONE SURVEY COMPLETE > 12 MONTHS": "IMAGING",
"XRAY BONE SURVEY COMPLETE >12 MONTHS": "IMAGING",
"XRAY BONE SURVEY INFANT": "IMAGING",
"XRAY BONE SURVEY LIMITED": "IMAGING",
"XRAY CHEST LFT/LAT DECUB 1VW": "IMAGING",
"XRAY CHEST OBLIQUES ONLY": "IMAGING",
"XRAY CHEST PA ONLY W/OBLIQUES": "IMAGING",
"XRAY CHEST PA ONLY WITH OBLIQUES": "IMAGING",
"XRAY CHEST RT/LAT DECUB 1VW": "IMAGING",
"XRAY CHEST SPEC VIEWS": "IMAGING",
"XRAY CHESTAPICAL LORDOTIC ONLY": "IMAGING",
"XRAY CLAVICLE-BILATERAL": "IMAGING",
"XRAY CLAVICLE-LEFT": "IMAGING",
"XRAY CLAVICLE-RIGHT": "IMAGING",
"XRAY CTRL CATH INSERT RENAL PELVIS": "IMAGING",
"XRAY CTRL CATH INSERT URETERAL": "IMAGING",
"XRAY CYSTOGRAM": "IMAGING",
"XRAY DACROCYSTOGRAM BILATERAL": "IMAGING",
"XRAY DACROCYSTOGRAM LEFT": "IMAGING",
"XRAY DACROCYSTOGRAM RIGHT": "IMAGING",
"XRAY DIGIT(S)TOES BILAT": "IMAGING",
"XRAY DIGIT(S)TOES LEFT": "IMAGING",
"XRAY DIGIT(S)TOES RIGHT": "IMAGING",
"XRAY DIGITS FINGER(S)": "IMAGING",
"XRAY ELBOW 2 VW BILATERAL": "IMAGING",
"XRAY ELBOW 2 VW LEFT": "IMAGING",
"XRAY ELBOW 2 VW RIGHT": "IMAGING",
"XRAY ELBOW 3 VW BILATERAL": "IMAGING",
"XRAY ELBOW 3 VW LEFT": "IMAGING",
"XRAY ELBOW 3 VW RIGHT": "IMAGING",
"XRAY ELBOW 4 VW BILATERAL": "IMAGING",
"XRAY ELBOW 4 VW LEFT": "IMAGING",
"XRAY ELBOW 4 VW RIGHT": "IMAGING",
"XRAY ELBOW CHURCH ARTH BILAT": "IMAGING",
"XRAY ELBOW CHURCH ARTH LT": "IMAGING",
"XRAY ELBOW CHURCH ARTH RT": "IMAGING",
"XRAY FEMUR 2 VW": "IMAGING",
"XRAY FEMUR 2 VW BILAT": "IMAGING",
"XRAY FEMUR 2 VW LEFT": "IMAGING",
"XRAY FEMUR 2 VW RIGHT": "IMAGING",
"XRAY FINGER (S) 1 VW BILATERAL": "IMAGING",
"XRAY FINGER (S) 2 VW OR > LEFT": "IMAGING",
"XRAY FINGER (S) 2 VW OR > RIGHT": "IMAGING",
"XRAY FINGER(S) 1 VW LEFT": "IMAGING",
"XRAY FINGER(S) 1 VW RIGHT": "IMAGING",
"XRAY FINGER(S) 2 VW OR > BILAT": "IMAGING",
"XRAY FISTULA ABSCESS SINUS TRACT": "IMAGING",
"XRAY FL ESO/UGI NO AIR(NO KUB)": "IMAGING",
"XRAY FL ESO/UGI NO AIR(W/KUB)": "IMAGING",
"XRAY FL ESOP/UGI AIR (NO KUB)": "IMAGING",
"XRAY FL ESOP/UGI W/AIR(W/KUB)": "IMAGING",
"XRAY FLUROSCOPY BY RAD": "IMAGING",
"XRAY FOOT 1 VW BILAT": "IMAGING",
"XRAY FOOT 1 VW LEFT": "IMAGING",
"XRAY FOOT 1 VW RIGHT": "IMAGING",
"XRAY FOOT 2 VW BILAT": "IMAGING",
"XRAY FOOT 2 VW LEFT": "IMAGING",
"XRAY FOOT 2 VW RIGHT": "IMAGING",
"XRAY FOOT 2 VW STANDING BILAT": "IMAGING",
"XRAY FOOT 2 VW STANDING LT": "IMAGING",
"XRAY FOOT 2 VW STANDING RT": "IMAGING",
"XRAY FOOT 3+ VW BILAT": "IMAGING",
"XRAY FOOT 3+ VW LEFT": "IMAGING",
"XRAY FOOT 3+ VW RIGHT": "IMAGING",
"XRAY FOOT 3+ VW STANDING BILAT": "IMAGING",
"XRAY FOOT 3+ VW STANDING LEFT": "IMAGING",
"XRAY FOOT 3+ VW STANDING RIGHT": "IMAGING",
"XRAY FOOT KITE BILAT": "IMAGING",
"XRAY FOOT KITE LT": "IMAGING",
"XRAY FOOT KITE RT": "IMAGING",
"XRAY FOOT STAND LAT ONLY BILAT": "IMAGING",
"XRAY FOOT STAND LAT ONLY LT": "IMAGING",
"XRAY FOOT STAND LATER ONLY RT": "IMAGING",
"XRAY FOOT STANDING DR HINZ LT": "IMAGING",
"XRAY FOOT STANDING DR HINZ RT": "IMAGING",
"XRAY FOOT STANDING HINZ BILAT": "IMAGING",
"XRAY FOR BONE AGE": "IMAGING",
"XRAY FOREARM": "IMAGING",
"XRAY FOREARM 2 VW BILATERAL": "IMAGING",
"XRAY FOREARM 2 VW LEFT": "IMAGING",
"XRAY FOREARM 2 VW RIGHT": "IMAGING",
"XRAY HAND 1 VW BILATERAL": "IMAGING",
"XRAY HAND 1 VW LEFT": "IMAGING",
"XRAY HAND 1 VW RIGHT": "IMAGING",
"XRAY HAND 2 VW": "IMAGING",
"XRAY HAND 2 VW BILATERAL": "IMAGING",
"XRAY HAND 2 VW LEFT": "IMAGING",
"XRAY HAND 2 VW RIGHT": "IMAGING",
"XRAY HAND 3+ VW": "IMAGING",
"XRAY HAND 3+ VW BILATERAL": "IMAGING",
"XRAY HAND 3+ VW LEFT": "IMAGING",
"XRAY HAND 3+ VW RIGHT": "IMAGING",
"XRAY HAND BETTS BILAT": "IMAGING",
"XRAY HAND BETTS LT": "IMAGING",
"XRAY HAND BETTS RT": "IMAGING",
"XRAY HAND BREWERTON BILAT": "IMAGING",
"XRAY HAND BREWERTON LT": "IMAGING",
"XRAY HAND BREWERTON RT": "IMAGING",
"XRAY HIP 1 VW": "IMAGING",
"XRAY HIP 1 VW BILAT": "IMAGING",
"XRAY HIP 1 VW LEFT": "IMAGING",
"XRAY HIP 1 VW RIGHT": "IMAGING",
"XRAY HIP 2 VW": "IMAGING",
"XRAY HIP 2 VW BILAT": "IMAGING",
"XRAY HIP 2 VW LEFT": "IMAGING",
"XRAY HIP 2 VW RIGHT": "IMAGING",
"XRAY HIP CHURCHILL ROUTINE BIL": "IMAGING",
"XRAY HIP CHURCHILL ROUTINE LT": "IMAGING",
"XRAY HIP CHURCHILL ROUTINE RT": "IMAGING",
"XRAY HUMERUS 1 VW BILATERAL": "IMAGING",
"XRAY HUMERUS 1 VW LEFT": "IMAGING",
"XRAY HUMERUS 1 VW RIGHT": "IMAGING",
"XRAY HUMERUS 2 VW BILATERAL": "IMAGING",
"XRAY HUMERUS 2 VW LEFT": "IMAGING",
"XRAY HUMERUS 2 VW RIGHT": "IMAGING",
"XRAY HUMERUS TRAN THORACIC BIL": "IMAGING",
"XRAY HUMERUS TRANS THORACIC LT": "IMAGING",
"XRAY HUMERUS TRANS THORACIC RT": "IMAGING",
"XRAY HYSTEROSALPINGOGRAM": "IMAGING",
"XRAY IV PYELOGR IVP W/ TOMOS": "IMAGING",
"XRAY IV PYELOGR IVP W/O TOMOS": "IMAGING",
"XRAY KNEE 1 OR 2 VIEW": "IMAGING",
"XRAY KNEE 1 OR 2 VW BILAT": "IMAGING",
"XRAY KNEE 1 OR 2 VW LEFT": "IMAGING",
"XRAY KNEE 1 OR 2 VW RIGHT": "IMAGING",
"XRAY KNEE 3 VIEW": "IMAGING",
"XRAY KNEE 3 VW BILAT": "IMAGING",
"XRAY KNEE 3 VW LEFT": "IMAGING",
"XRAY KNEE 3 VW RIGHT": "IMAGING",
"XRAY KNEE 4 VW": "IMAGING",
"XRAY KNEE 4+ VW BILAT": "IMAGING",
"XRAY KNEE 4+ VW LEFT": "IMAGING",
"XRAY KNEE 4+VW RIGHT": "IMAGING",
"XRAY KNEE CHURCH/FAURE BILAT": "IMAGING",
"XRAY KNEE CHURCH/FAURE LT": "IMAGING",
"XRAY KNEE CHURCH/FAURE RT": "IMAGING",
"XRAY KNEE JT STRESS VWS BILAT": "IMAGING",
"XRAY KNEE JT STRESS VWS LEFT": "IMAGING",
"XRAY KNEE JT STRESS VWS RIGHT": "IMAGING",
"XRAY KNEE MERCHANT BILAT": "IMAGING",
"XRAY KNEE MERCHANT LT": "IMAGING",
"XRAY KNEE MERCHANT RT": "IMAGING",
"XRAY KNEE SCHULTZ BILAT": "IMAGING",
"XRAY KNEE SCHULTZ LT": "IMAGING",
"XRAY KNEE SCHULTZ RT": "IMAGING",
"XRAY KNEE STANDING BILAT": "IMAGING",
"XRAY KNEE WEBER BILAT": "IMAGING",
"XRAY KNEE WEBER LT": "IMAGING",
"XRAY KNEE WEBER RT": "IMAGING",
"XRAY LEG LENGTHS 1 FILM": "IMAGING",
"XRAY LOW EXT INF<12 MO LEFT": "IMAGING",
"XRAY LOW EXT INF<12 MOS BILAT": "IMAGING",
"XRAY LOWER EXT INF<12 MO RIGHT": "IMAGING",
"XRAY LOWER LEG/TIB/FIB BILAT": "IMAGING",
"XRAY LOWER LEG/TIB/FIB LEFT": "IMAGING",
"XRAY LOWER LEG/TIB/FIB RIGHT": "IMAGING",
"XRAY LUM SPINE AP LAT FLEX EXT": "IMAGING",
"XRAY LUM SPINE AP LAT W/OBL FLEX/EXT": "IMAGING",
"XRAY LUMB SPINE 2VW FLEX/EXT": "IMAGING",
"XRAY LUMBAR 2 OR 3 VW": "IMAGING",
"XRAY MAMMARY DUCT": "IMAGING",
"XRAY MAMMARY DUCT/GALA/MUL/LFT": "IMAGING",
"XRAY MAMMARY DUCT/GALA/MULT/RT": "IMAGING",
"XRAY MAMMARY DUCT/GALA/SGL/LFT": "IMAGING",
"XRAY MAMMARY DUCT/GALA/SGL/RT": "IMAGING",
"XRAY MAMMARY DUCTS": "IMAGING",
"XRAY MAMMO CONED COMP VW BILAT": "IMAGING",
"XRAY MAMMO CONED VW BILAT": "IMAGING",
"XRAY MAMMO CONED VW LEFT": "IMAGING",
"XRAY MAMMO CONED VW RIGHT": "IMAGING",
"XRAY MAMMO MAGNIFICATION VW BI": "IMAGING",
"XRAY MAMMO MAGNIFICATION VW LT": "IMAGING",
"XRAY MAMMO MAGNIFICATION VW RT": "IMAGING",
"XRAY MAMMO MAGNIFICATION VW/BI": "IMAGING",
"XRAY MAMMOGRAM DIAGNOSTIC BILA": "IMAGING",
"XRAY MAMMOGRAM DIAGNOSTIC BILAT": "IMAGING",
"XRAY MAMMOGRAM DIAGNOSTIC LEFT": "IMAGING",
"XRAY MAMMOGRAM DIAGNOSTIC LT": "IMAGING",
"XRAY MAMMOGRAM DIAGNOSTIC RT": "IMAGING",
"XRAY MAMMOGRAM DIAGNOSTIC UNIL": "IMAGING",
"XRAY MAMMOGRAM SCREENING BILAT": "IMAGING",
"XRAY MYELOGRAPHY 2+ AREA/SPINE": "IMAGING",
"XRAY MYELOGRAPHY CERV SPINE": "IMAGING",
"XRAY MYELOGRAPHY LUMBAR SPINE": "IMAGING",
"XRAY MYELOGRAPHY THORAC SPINE": "IMAGING",
"XRAY NEPHROSTOGRAM LOOPOGRAM": "IMAGING",
"XRAY RIBS 2 VW UNILAT RIGHT": "IMAGING",
"XRAY RIBS 2 VW UNILAT-LEFT": "IMAGING",
"XRAY RIBS BILATERAL": "IMAGING",
"XRAY RIBS, UNILAT, PA CHEST": "IMAGING",
"XRAY RIBS,UNI LFT W/PA CHEST": "IMAGING",
"XRAY RIBS,UNI/RT W/PA CHEST": "IMAGING",
"XRAY SCAPULA BILATERAL": "IMAGING",
"XRAY SCAPULA LEFT": "IMAGING",
"XRAY SCAPULA RIGHT": "IMAGING",
"XRAY SCOLIOSIS SERIES(PANEL)": "IMAGING",
"XRAY SCOLIOSIS STAND 1 OR 2 VW": "IMAGING",
"XRAY SHOUL AC CHURCH INSTA BIL": "IMAGING",
"XRAY SHOUL AC CHURCH INSTA LT": "IMAGING",
"XRAY SHOUL AC CHURCH INSTA RT": "IMAGING",
"XRAY SHOUL CHURCH ARTH BIL": "IMAGING",
"XRAY SHOUL CHURCH ARTH LT": "IMAGING",
"XRAY SHOUL CHURCH ARTH RT": "IMAGING",
"XRAY SHOUL TRANS THORACIC RT": "IMAGING",
"XRAY SHOULD AC CHURCH ARTH BIL": "IMAGING",
"XRAY SHOULD AC CHURCH ARTH LT": "IMAGING",
"XRAY SHOULD ACROMIAL ARCH BIL": "IMAGING",
"XRAY SHOULD ACROMIAL ARCH LT": "IMAGING",
"XRAY SHOULD ACROMIAL ARCH RT": "IMAGING",
"XRAY SHOULD CHURCH IMPING BIL": "IMAGING",
"XRAY SHOULD CHURCH IMPING LT": "IMAGING",
"XRAY SHOULD CHURCH IMPING RT": "IMAGING",
"XRAY SHOULD CHURCH INSTA BILAT": "IMAGING",
"XRAY SHOULD CHURCH INSTA LT": "IMAGING",
"XRAY SHOULD CHURCH INSTA RT": "IMAGING",
"XRAY SHOULD CHURCH SCREEN BIL": "IMAGING",
"XRAY SHOULD CHURCH SCREEN LT": "IMAGING",
"XRAY SHOULD CHURCH SCREEN RT": "IMAGING",
"XRAY SHOULD CHURCH TRAUMA BIL": "IMAGING",
"XRAY SHOULD CHURCH TRAUMA LT": "IMAGING",
"XRAY SHOULD CHURCH TRAUMA RT": "IMAGING",
"XRAY SHOULD TRANS THORACIC BIL": "IMAGING",
"XRAY SHOULD TRANS THORACIC LT": "IMAGING",
"XRAY SHOULD/AC CURCH ARTH RT": "IMAGING",
"XRAY SHOULDER 1 VW BILAT": "IMAGING",
"XRAY SHOULDER 1 VW LEFT": "IMAGING",
"XRAY SHOULDER 1 VW RIGHT": "IMAGING",
"XRAY SHOULDER 2 VW BILATERAL": "IMAGING",
"XRAY SHOULDER 2 VW LEFT": "IMAGING",
"XRAY SHOULDER 2 VW RIGHT": "IMAGING",
"XRAY SHOULDER 3 VW BILATERAL": "IMAGING",
"XRAY SHOULDER 3 VW LEFT": "IMAGING",
"XRAY SHOULDER 3 VW RIGHT": "IMAGING",
"XRAY SHOULDER 4 VW BILATERAL": "IMAGING",
"XRAY SHOULDER 4 VW LEFT": "IMAGING",
"XRAY SHOULDER 4 VW RIGHT": "IMAGING",
"XRAY SHOULDER FAURE BILAT": "IMAGING",
"XRAY SHOULDER FAURE LT": "IMAGING",
"XRAY SHOULDER FAURE RT": "IMAGING",
"XRAY SHOULDER GAENSLEN BILAT": "IMAGING",
"XRAY SHOULDER GAENSLEN LT": "IMAGING",
"XRAY SHOULDER GAENSLEN RT": "IMAGING",
"XRAY SHOULDER GRASHEY BILAT": "IMAGING",
"XRAY SHOULDER GRASHEY LT": "IMAGING",
"XRAY SHOULDER GRASHEY RT": "IMAGING",
"XRAY SHOULDER SCHULTZ BILAT": "IMAGING",
"XRAY SHOULDER SCHULTZ LT": "IMAGING",
"XRAY SHOULDER SCHULTZ RT": "IMAGING",
"XRAY SIALOGRAM": "IMAGING",
"XRAY SIALOGRAM RIGHT": "IMAGING",
"XRAY SPINE ONE VIEW": "IMAGING",
"XRAY STRESS VIEW ANY JOINT BY DOC": "IMAGING",
"XRAY TEAR DUCT": "IMAGING",
"XRAY THORACIC SPINE 3VW W/SWI": "IMAGING",
"XRAY THORACOLUMBAR JUNCTION 2 VIEWS": "IMAGING",
"XRAY THUMB ROBERTS BILAT": "IMAGING",
"XRAY THUMB ROBERTS LT": "IMAGING",
"XRAY THUMB ROBERTS RT": "IMAGING",
"XRAY TMJ ARTHROGRAM": "IMAGING",
"XRAY TMJ LEFT": "IMAGING",
"XRAY TMJ RIGHT": "IMAGING",
"XRAY TMJ UNILAT": "IMAGING",
"XRAY TOMOGRAM": "IMAGING",
"XRAY UPPER EXT < 12 MONTHS BIL": "IMAGING",
"XRAY UPPER EXT < 12 MONTHS LEFT": "IMAGING",
"XRAY UPPER EXT < 12 MONTHS RT": "IMAGING",
"XRAY URETHROCYSTOGRAM": "IMAGING",
"XRAY URETHROCYSTOGRAM VOIDING": "IMAGING",
"XRAY VENOGRAM LEG BILAT": "IMAGING",
"XRAY VENOGRAM LEG LEFT": "IMAGING",
"XRAY VENOGRAM LEG RIGHT": "IMAGING",
"XRAY WRIST 2 VW": "IMAGING",
"XRAY WRIST 2 VW BILATERAL": "IMAGING",
"XRAY WRIST 2 VW LEFT": "IMAGING",
"XRAY WRIST 2 VW RIGHT": "IMAGING",
"XRAY WRIST 3 VW MINIMUM BILATERAL": "IMAGING",
"XRAY WRIST 3 VW MINIMUM LEFT": "IMAGING",
"XRAY WRIST 3 VW MINIMUM RIGHT": "IMAGING",
"XRAY WRIST 3+ VW": "IMAGING",
"XRAY WRIST CARP TUNNEL BIL ": "IMAGING",
"XRAY WRIST CARP TUNNEL LT": "IMAGING",
"XRAY WRIST CARP TUNNEL ONLY RT": "IMAGING",
"XRAY WRIST NAVICULAR ONLY BIL": "IMAGING",
"XRAY WRIST NAVICULAR ONLY LFT": "IMAGING",
"XRAY WRIST NAVICULAR ONLY RT": "IMAGING",
"XRAY WRIST NAVICULAR VW BILAT": "IMAGING",
"XRAY WRIST NAVICULAR VW LEFT": "IMAGING",
"XRAY WRIST NAVICULAR VW RIGHT": "IMAGING"
}
|
#!/usr/bin/env python
# Copyright (c) 2012 Google Inc. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""
Verifies that setting SDKROOT works.
"""
import TestGyp
import os
import subprocess
import sys
if sys.platform == 'darwin':
print "This test is currently disabled: https://crbug.com/483696."
sys.exit(0)
test = TestGyp.TestGyp(formats=['ninja', 'make', 'xcode'])
def GetSDKPath(sdk):
"""Return SDKROOT if the SDK version |sdk| is installed or empty string."""
DEVNULL = open(os.devnull, 'wb')
try:
proc = subprocess.Popen(
['xcodebuild', '-version', '-sdk', 'macosx' + sdk, 'Path'],
stdout=subprocess.PIPE, stderr=DEVNULL)
return proc.communicate()[0].rstrip('\n')
finally:
DEVNULL.close()
def SelectSDK():
"""Select the oldest SDK installed (greater than 10.6)."""
for sdk in ['10.6', '10.7', '10.8', '10.9']:
path = GetSDKPath(sdk)
if path:
return True, sdk, path
return False, '', ''
# Make sure this works on the bots, which only have the 10.6 sdk, and on
# dev machines which usually don't have the 10.6 sdk.
sdk_found, sdk, sdk_path = SelectSDK()
if not sdk_found:
test.fail_test()
test.write('sdkroot/test.gyp', test.read('sdkroot/test.gyp') % sdk)
test.run_gyp('test.gyp', '-D', 'sdk_path=%s' % sdk_path,
chdir='sdkroot')
test.build('test.gyp', test.ALL, chdir='sdkroot')
test.pass_test()
|
#!/usr/bin/env python
import re
import nltk
import string
from tika import parser
def ocr_cleaner(text):
"""This function takes in input text, performs various regex and non-regex based substitutions
and then returns a line-by-line representation of each sentence extracted from raw OCR data."""
text = text.lower().replace('\n', ' ').replace('\r', ' ').replace('\t', ' ').strip() # replace all whitespace, lower
text = ' '.join(text.split()) # remove consecutive spaces
text = re.sub(r'(?<=[a-z]{3})[.]', '.\n', text)
text = text.encode('ascii', errors='ignore').decode(encoding='utf8').replace(r'\\', '').replace('"', '')
text = re.sub(r'(?<=nae)', '\n', text)
text = re.sub(r'(?<=dae)', '\n', text)
text = text.replace('life histories of cascadia butterflies', '').replace('\\', '').replace('|', '')
text = text.replace('adult biology', '').replace('immature stage biology', '')
text = text.replace('description of immature stages', '').replace('discussion', '')
text = re.sub(r'([0-9]){3}', '', text)
text = re.sub(r'([i])\b', '', text)
text = re.sub(r'(family|subfamily).*', '', text)
text = text.replace('-', ' ').replace('tlie', 'the').replace('ihis', 'this').replace('ditilicult', 'difficult')
text = re.sub(r'^\s*$', '', text)
text = ' '.join(text.split()) # remove consecutive spaces
text = re.sub(r'(?<=[a-z]{4})[.]', '.\n', text)
text = text.strip()
text = re.sub(r'[.,();\']', '', text)
return text
def get_tokens_from_file(file_path, column_index):
"""Opens a file safely, then creates and returns a list of lists containing tokenized
sentences from the file."""
line_list = []
with open(file_path, 'r', encoding='utf8') as f:
content = f.readlines()
for i, line in enumerate(content):
line_list.append(line.split())
return line_list
printable = set(string.printable)
raw = parser.from_file('sample.pdf') # parse OCR text from file
text = raw['content'] # grab textual content
lines = ocr_cleaner(text) # send to line cleaning function
with open("raw.txt", 'w', encoding='utf8') as f:
f.write(lines)
line_list = get_tokens_from_file("raw.txt", 1)
|
def square_list(start,end):
L=[]
while start**2<=end**2:
L.append(start**2)
start+=1
return L
x=int(input("Please enter a number you want to begin with:"))
y=int(input("Please enter an ending number:"))
print(square_list(x,y))
print(square_list(1,100))
|
import airflow
from airflow.models import DAG
from datetime import datetime
from airflow.hooks.postgres_hook import PostgresHook
from airflow.utils.decorators import apply_defaults
from airflow.contrib.operators.postgres_to_gcs_operator import PostgresToGoogleCloudStorageOperator
from airflow_training.operators.http_to_gcs_operator import HttpToGcsOperator
args = {
"owner": "Miha",
"start_date": datetime(2019,9,20),
}
dag = DAG(
dag_id="exercise4",
default_args=args,
schedule_interval="0 0 * * *",
)
pgsl_to_gcs = PostgresToGoogleCloudStorageOperator(
task_id="transfer_data_from_postgres",
sql="SELECT * FROM land_registry_price_paid_uk WHERE transfer_date = '{{ ds }}'",
bucket="airflow-training-data-1983",
filename="land_registry/{{ ds }}/properties_{}.json",
postgres_conn_id="GoogleCloudSQL-miha",
dag=dag,
)
currency = "EUR"
transfer_currency = HttpToGcsOperator(
task_id="get_currency_" + currency,
method="GET",
endpoint="history?start_at={{yesterday_ds}}&end_at={{ds}}&symbols=EUR&base=GBP",
http_conn_id="airflow-training-currency-http",
gcs_path="currency/{{ ds }}-" + currency + ".json",
gcs_bucket="airflow-training-data-1983",
dag=dag,
)
pgsl_to_gcs >> transfer_currency
|
import os
def rename_files():
file_list = os.listdir(r"/Users/Angadlamba21/Documents/Myprojects/python/udacity/prank")
print file_list
saved_path = os.getcwd()
os.chdir(r"/Users/Angadlamba21/Documents/Myprojects/python/udacity/prank")
for file_name in file_list:
os.renames(file_name, file_name.translate(None, "0123456789"))
os.chdir(saved_path)
rename_files()
|
import requests
image_url = "https://ajeas.godohosting.com/img/F19082100001_02.jpg"
headers = {'User-agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.76 Safari/537.36', 'Accept':'text/html,application/xhtml+xml,applicpipation/xml;q=0.9,*/*;q=0.8','Accept-Encoding':'gzip,deflate,sdch', 'Referer': 'https://foodspring.co.kr'}
r = requests.get(image_url, headers = headers)
print(r)
|
"""
curves @ utils
parses paths to curve.mb's from assets/crvSrc folder
EXAMPLES:
#imports the first curve in crvSrc folder
mc.file(rigLib.utils.curves.curvesList[0], i=1)
#prints a list of curves in crvSrc folder
print rigLib.utils.curves.curvesList
"""
import maya.cmds as mc
import glob
from rigLib.config import projectPath
from rigLib.utils.name import removeSuffix
fp = projectPath + '/assets/curveSrc/%s'
curvesValueList = [ f.replace('\\','/') for f in glob.glob(fp %'*.mb')]
curvesKeyList = [f.split('/')[-1].replace('_crv.mb', '') for f in curvesValueList]
curvesDict = dict(zip(curvesKeyList,curvesValueList))
def combineCurves(selCrvs = mc.ls(sl=1)):
"""
freezes and combines curves shapes under one transform
@param curves: the list of curves (with transform nodes) to combine
"""
mc.makeIdentity(selCrvs, a=1)
crvGrp = mc.group(selCrvs[0], em=1)
shapes = mc.listRelatives(selCrvs,s=1)
mc.parent(shapes, crvGrp, s=1 , r=1)
returnGrp = mc.duplicate(crvGrp, n = selCrvs[0] +'_crv')
mc.delete(crvGrp,selCrvs)
return returnGrp
def curveFromMesh(obj = mc.ls(sl=1), offset = 0):
"""
creates a curve based on the edges of a source mesh
@param obj: source object (selection by default)
@param offset: gives the option to offset crv from the source mesh
"""
#clear obj from selection and duplicate it
mc.select(clear=1)
dup = mc.duplicate(obj, n = '%s.dupMesh'%obj)
#extrude dup mesh for offset if you want
faceCount = mc.polyEvaluate(dup, face=1)
faceList = ['%s.f[%s]'%(dup[0], i) for i in range(0, faceCount)]
mc.polyExtrudeFacet(faceList, ltz=offset, ch=0)
#convert extruded faces to a list of edges
edgeList = mc.polyListComponentConversion(mc.ls(selection =1),ff=1, te=1)
edgeList = mc.filterExpand(edgeList, sm=32)
edgeCurves = []
for e in edgeList:
crv = mc.polyToCurve(e, degree=1, ch=0)
edgeCurves.append(str(crv[0]))
mc.delete(dup)
comboCrv = combineCurves(edgeCurves)[0]
comboCrv = mc.rename(comboCrv,'%s_crv'%obj)
mc.xform(comboCrv, cp=1)
def attachLocsToCrv(srcCrv, locNum, prefix = None, breakRotation = True):
"""
attaches locators evenly spaced out along a curve
@param srcCrv, dang ol' curve ya want yer locs on
@param locNum, the number of locs set tah yer likin'
@param prefix, the prefix ya want fer stuff
@param breakRotation, rotation connections can cuz a whoppin' mess cowboy!
@return list( str )
"""
locators = []
step = 1/(locNum - float(1))
for i in range(0,locNum):
if prefix is None:
prefix = removeSuffix(srcCrv)
loc = mc.spaceLocator(n = prefix + str(i+1) + '_loc')
path = mc.pathAnimation(
loc,
n = 'moPath',
c = srcCrv,
fm = 1,
f = 1,
fa = 'x',
ua = 'y'
)
mc.cutKey(path, time = (0,10000), clear = True)
if breakRotation:
for attr in ['.rx','.ry','.rz']:
conn = mc.listConnections(loc[0]+ attr , source = 1 , p = 1)[0]
mc.disconnectAttr(conn, loc[0] + attr)
mc.setAttr(loc[0] + attr, 0)
iStep = i * step
mc.setAttr(path + '.uValue', iStep)
locators.append(loc[0])
return locators
def curveBetweenPoints(pointA, pointB, prefix = 'new', constrainCurve = False):
"""
makes a curve between two points
@param pointA: object whos world space translation will be used for point A
@param prefix, str: the prefix of the curve
@param constrainCurve bool: should this curve be weighted to it points?
"""
transforms = [mc.xform(point, q=1, t=1, ws=1) for point in [pointA, pointB]]
abCurve = mc.curve(n = prefix + '_crv',d =1, p = [transforms[0],transforms[1]])
if constrainCurve:
mc.cluster(abCurve+ '.cv[0]', n = prefix + 'crvPointA_cls', wn = [pointA, pointA], bs =1)
mc.cluster(abCurve + '.cv[1]', n = prefix + 'crvPointB_cls', wn = [pointB, pointB], bs =1)
return abCurve
|
import matplotlib.pyplot as plt
import numpy as np
u=np.linspace(-2,2,200)
v=np.linspace(-1,1,100)
X,Y=np.meshgrid(u,v)
z=X**2/25+Y**2/4
plt.pcolor(z)#for pseudocolor
plt.colorbar()
plt.show()
plt.pcolor(z, cmap='gray')
plt.colorbar()
plt.show()
plt.pcolor(z, cmap='autumn')
plt.colorbar()
plt.show()
plt.pcolor(z)
plt.colorbar()
plt.axis('tight')
plt.show()
plt.pcolor(X,Y,z)
plt.colorbar()
plt.show()
plt.contour(z)
plt.show()
plt.contour(z,30)
plt.contour(X,Y,z, 30)
plt.show()
|
#-*- coding=utf-8 -*-
import requests
from hashlib import md5
import copy
from config import *
url = 'https://payjs.cn/api/native'
data = {'mchid': PAYJS_ID,
'total_fee': '1',
'out_trade_no': '2017122712581',
'body': 'test'}
def get_sign(data):
str_d = sorted(['='.join(i) for i in data.items()], key=lambda x: x[0])
str_d.append('key={}'.format(PAYJS_KEY))
str_ = '&'.join(str_d)
a = md5(str_.encode('utf-8'))
return a.hexdigest().upper()
def getqr(money, tradeid, info='faka', feedback=None):
sd = copy.deepcopy(data)
sd['total_fee'] = str(int(money * 100))
sd['out_trade_no'] = str(tradeid)
sd['body'] = info
if feedback != None:
sd['notify_url'] = feedback
sign = get_sign(sd)
sd['sign'] = sign
try:
r = requests.post(url, data=sd)
return r.json()['code_url']
except Exception as e:
print(e)
return False
|
class Solution:
# @param A : list of integers
# @param B : integer
# @return a list of list of integers
def combinationSum(self, A, B):
"""
This wss one of those ones where I do a first solution to check for correctness,
expecting that InterviewBit will fail it for efficiency, and that after that I
will work on optimizing it/coming up with a more efficient approach, but instead
it passes just fine.
"""
combo_sums = []
combos = [[]]
A = sorted([x for x in A if x <= B])
for num in A:
temp = []
for combo in combos:
new_combo = combo + [num]
total = sum(new_combo)
if total == B and new_combo not in combo_sums:
combo_sums.append(new_combo)
elif total < B:
temp.append(new_combo)
combos += temp
return combo_sums
|
"""
Tests for cinder api
"""
from __future__ import absolute_import, division, unicode_literals
from twisted.trial.unittest import SynchronousTestCase
from mimic.test.helpers import json_request
from mimic.rest.cinder_api import CinderApi
from mimic.test.fixtures import APIMockHelper
class CinderTests(SynchronousTestCase):
"""
Tests for cinder using the Cinder Api plugin.
"""
def setUp(self):
"""
Initialize core and root
"""
cinder_api = CinderApi(['DFW'])
self.helper = APIMockHelper(self, [cinder_api])
self.root = self.helper.root
self.uri = self.helper.uri
def test_get_blockstorage_volume_list(self):
"""
Requesting block storage volumes for a tenant returns 200 and an empty list
if no volumes are available for the given tenant
http://developer.openstack.org/api-ref-blockstorage-v2.html#getVolumesSimple
"""
(response, content) = self.successResultOf(json_request(
self, self.root, b"GET", self.uri + '/volumes'))
self.assertEqual(200, response.code)
self.assertEqual(content, {'volumes': []})
|
# -*- coding: utf-8 -*-
"""
Main script to train and export NN Inverse models for the Holzapfel Material.
Input: Stress (kPa) - Strain curves + cube dimensions + fiber orientation
Output: Material parameters
"""
import numpy as np
from random import seed
import torch
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt
from time import time
from pyDOE import lhs
import PreProcess
import Metamodels
import PostProcess
# Optimizer settings
RUN_NAME = 'MyocardiumNNR_'
EPOCHS = 500
LEARNING_RATE = 0.001
HIDDEN_DIM = 50
NUM_OUTPUT = 2
N_STRAIN = 30 # Originally 30 for the model w/ Strain
DEPTH = 3
STRAIN_FEATURE = True
PRINT_INT = 5 # Print gif every other PRINT_INT epoch
DEVICE = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
# Training and testing data (number of FEBio simulations)
num_train_list = [8000, 100, 250, 500, 1000, 1500, 2000, 3000, 4000, 5000, 6000, 7000]
valid_sets = list(range(10001,11001))
n_val = len(valid_sets)
# Reproduce
np.random.seed(1234)
seed(1234)
torch.manual_seed(1234)
# Initialize val data, test data and learning curve dictionary
if STRAIN_FEATURE:
NUM_FEATURES = 1+N_STRAIN*2
else:
NUM_FEATURES = N_STRAIN*2
TestData ={'1':[],'2':[],'3':[],'4':[],'5':[],'6':[],'7':[],'8':[],'9':[]}
lc_stats = {'num_train':[],'train_time':[], 'MAE_train': [], 'MAPE_train': [], 'R2_train': [],'MAE_val': [], 'MAPE_val': [], 'R2_val': [] }
# Initialize data class
TestData = PreProcess.OgdenData()
# Load Validation data
lhd_val = lhs(1, samples=n_val) # Sample strain amplitude for validation
Fx_val, Fz_val, matl_val = PreProcess.sort_OgdenData(TestData, valid_sets)
Strain_val = PreProcess.sample_OgdenStrain(lhd_val,STRAIN_FEATURE)
Fx_val, Fz_val = PreProcess.interpolate_Ogden_ss(TestData, n_val, N_STRAIN ,Fx_val, Fz_val , Strain_val)
# Loop Training sets
for kk in range(0, len(num_train_list)):
# Load Training set
train_sets = list(range(1,num_train_list[kk]+1))
n_train = len(train_sets)
print(f'TRAIN_n...{n_train+0:03}')
BATCH_SIZE = min(n_train,100)
Fx_train, Fz_train, matl_train = PreProcess.sort_OgdenData(TestData,train_sets)
# Sample the strain Amplitudes, Shear:0.3-0.4 and Uniaxial: 0.10-0.15
lhd_train = lhs(1, samples=n_train)
Strain_train = PreProcess.sample_OgdenStrain(lhd_train, STRAIN_FEATURE)
# Interpolate stress strain curve
Fx_train, Fz_train = PreProcess.interpolate_Ogden_ss(TestData, n_train, N_STRAIN, Fx_train, Fz_train , Strain_train)
# Assemble Stress Vectors
X_train = PreProcess.assemble_OgdenX(Strain_train, Fx_train, Fz_train, STRAIN_FEATURE)
X_val = PreProcess.assemble_OgdenX(Strain_val, Fx_val, Fz_val, STRAIN_FEATURE)
Y_train = matl_train
Y_val = matl_val
# Scale both input and output
Xscaler, Yscaler = StandardScaler(), Metamodels.OgdenScaler()
Xscaler.fit(X_train)
Y_train_scaled = Yscaler.transform(Y_train)
Y_val_scaled = Yscaler.transform(Y_val)
# Add noise to training data
# noise = np.random.normal(0,.001, X_train.shape)
noise = None
# Prepare data to Torch compatible
X_train_tensor, train_data, train_loader = Metamodels.scaled_to_tensor(DEVICE, Xscaler, X_train, Y_train, BATCH_SIZE, Yscaler, noise)
X_val_tensor, val_data, val_loader = Metamodels.scaled_to_tensor(DEVICE, Xscaler, X_val, Y_val, n_val ,Yscaler)
# Initialize utils for post processing
export = PostProcess.ExportData('BWD_Ogden', RUN_NAME + str(n_train) )
loss_stats = {'train': [], "val": [] }
epochFitImg = []
fig, (ax1,ax2) = plt.subplots(2,1,figsize=(10,14))
# Set up neural network metamodel
model = Metamodels.NN(feature_dim=NUM_FEATURES, hidden_dim=HIDDEN_DIM, output_dim=NUM_OUTPUT, depth = DEPTH, Ogden_BWD = True)
optimizer = torch.optim.Adam(model.parameters(), lr=LEARNING_RATE)
loss_func = torch.nn.L1Loss()
train_step = Metamodels.make_train_step(model, loss_func, optimizer)
# BEGIN TRAINNING
start = time()
for epoch in range(1,EPOCHS+1):
# Initialize train and validation error
train_epoch_loss = 0
val_epoch_loss = 0
# Batch training data
for x_batch, y_batch in train_loader:
# Send mini-batches to the device
x_batch, y_batch = x_batch.to(DEVICE), y_batch.to(DEVICE)
train_loss = train_step(x_batch, y_batch)
train_epoch_loss += train_loss
# Stop training and batch validation data
with torch.no_grad():
for x_val_batch, y_val_batch in val_loader:
x_val_batch = x_val_batch.to(DEVICE)
y_val_batch = y_val_batch.to(DEVICE)
model.eval()
yhat = model(x_val_batch)
val_loss = loss_func(y_val_batch, yhat)
val_epoch_loss += val_loss.item()
print(f'Epoch {epoch+0:03}: | Train Loss: {train_epoch_loss/len(train_loader):.5f} | Val Loss: {val_epoch_loss/len(val_loader):.5f}')
loss_stats['train'].append(train_epoch_loss/len(train_loader))
loss_stats['val'].append(val_epoch_loss/len(val_loader))
with torch.no_grad():
model.eval()
fX_val_tensor = model(X_val_tensor)
fX_val_scaled = fX_val_tensor.data.numpy()
fX_val = Yscaler.inverse_transform(fX_val_scaled)
fX_train_tensor = model(X_train_tensor)
fX_train_scaled = fX_train_tensor.data.numpy()
fX_train = Yscaler.inverse_transform(fX_train_scaled)
# Generate gif for Training of star set
export.OgdenParam_scatter(Y_val,fX_val, epoch, val_epoch_loss/len(val_loader), ax1, ax2)
fig.canvas.draw() # draw the canvas, cache the renderer
image = np.frombuffer(fig.canvas.tostring_rgb(), dtype='uint8')
image = image.reshape(fig.canvas.get_width_height()[::-1] + (3,))
if (epoch==1) or (epoch % PRINT_INT == 0):
epochFitImg.append(image)
# Calculate Run Time
end = time()
run_time = (end - start)/60
# Export total errors after training
lc_stats['num_train'].append(n_train)
lc_stats['train_time'].append(run_time)
lc_stats = export.compute_error(Y_train_scaled, fX_train_scaled, lc_stats, 'train')
lc_stats = export.compute_error(Y_val_scaled, fX_val_scaled, lc_stats, 'val')
export.dict_to_csv(lc_stats,'LC')
export.dict_to_csv(loss_stats,'EpochLoss')
export.OgdenParam_scatter(Y_val,fX_val, epoch, val_epoch_loss/len(val_loader), ax1, ax2, final=True)
export.epoch_curve(loss_stats)
# Save training gif
export.save_gif(n_train, epochFitImg)
# Export Trained NN
export.trained_NNs(Xscaler, model, n_train, HIDDEN_DIM, NUM_FEATURES, NUM_OUTPUT, Yscaler, DEPTH)
# Save learning curve
export.learning_curve(num_train_list,lc_stats['MAE_train'],lc_stats['MAE_val'],'MAE')
|
import sys
from time import sleep
import pytest
# sys.path.append("E:\College\SPRING 2021\\CMPN203\\"
# "project\\Flickr-Photos\\Flickr-Photos\\Testing\\Web")
from common.sel_helper import SelHelper
from pageobject.explore.explore import ExploreLocator, Explore
from pageobject.generalmethods.general_methods import GeneralMethods
TIME_TO_WAIT = 30
FILTER_EXISTS = False
LAYOUT_EXISTS = True
class TestExploreLinks(object):
helper = SelHelper()
explore = Explore(helper, TIME_TO_WAIT, FILTER_EXISTS, LAYOUT_EXISTS)
mock_methods = GeneralMethods(helper)
LOCATOR_LIST = explore.LOCATOR_LIST
driver = None
@pytest.fixture()
def setup(self):
driver = self.helper.init_chrome_driver()
driver.maximize_window()
self.helper.implicit_wait(30)
self.mock_methods.login()
sleep(3)
self.helper.go_to(self.explore.link)
sleep(10)
yield
self.helper.quit()
# @pytest.mark.skip
def test_driver(self, setup):
pass
# @pytest.mark.skip
def test_subnav_links(self, setup):
assert self.explore.test_subnav_links(30)
# @pytest.mark.skip
def test_layout(self, setup):
if not self.explore.layout_exists:
pytest.skip("explore doesn't have layout selection")
assert self.explore.select_layout("LAYOUT_STORY")
sleep(5)
# @pytest.mark.skip
def test_click_photo(self, setup):
assert self.explore.check_click_photo_link()
sleep(5)
|
import numpy as np
file = "Day3/inputnaomi.txt"
with open(file,'r') as f:
wires = [row.split(',') for row in f.readlines()]
f.close()
def intersection_present(start1, finish1, start2, finish2):
xint, yint = 0,0
if start1[0]==finish1[0]:
if start2[0]==finish2[0]:
return False, [xint, yint]
xint=start1[0]
yint=start2[1]
if min(start2[0],finish2[0]) <= xint and xint <= max(start2[0],finish2[0]):
if min(start1[1],finish1[1]) <= yint and yint <= max(start1[1],finish1[1]):
#print([xint,yint,manhattan([xint,yint])])
return True, [xint,yint]
if start1[1]==finish1[1]:
if start2[1]==finish2[1]:
return False, [xint, yint]
yint=start1[1]
xint=start2[0]
if min(start1[0],finish1[0]) <= xint and xint <= max(start1[0],finish1[0]):
if min(start2[1],finish2[1]) <= yint and yint <= max(start2[1],finish2[1]):
#print([xint,yint,manhattan([xint,yint])])
return True, [xint,yint]
return False, [xint, yint]
def manhattan(x):
return abs(x[0])+abs(x[1])
wire1_coords =
wire2_coords = []
def traverse_wire(wire,nrows):
current=[0,0]
wire_coords=[]
nsteps=0
for line in wire[:nrows]:
line.strip()
wire_coords.append(current.copy())
if line[0]=="U":
current[1]+=int(line[1:])
elif line[0]=="D":
current[1]-=int(line[1:])
elif line[0]=="R":
current[0]+=int(line[1:])
else:
current[0]-=int(line[1:])
nsteps+=int(line[1:])
wire_coords.append(current.copy())
return wire_coords, nsteps
# Part 1
wire1_coords=traverse_wire(wires[0],len(wires[0]))[0]
wire2_coords=traverse_wire(wires[1], len(wires[1]))[0]
def get_intersections(wire1,wire2):
return [intersection_present(wire1[i],wire1[i+1],wire2[j],wire2[j+1]) \
for i in range(len(wire1)-1) for j in range(len(wire2)-1)]
intersections=get_intersections(wire1_coords,wire2_coords)
true_intersections=[[intersections[i][1], manhattan(intersections[i][1])] for i in range(len(intersections)) if intersections[i][0]==True]
true_intersections.sort(key = lambda x: x[1])
print(true_intersections[0])
min_steps=-1
for i in range(len(wire1_coords)):
for j in range(len(wire2_coords)):
w1,nsteps1 = traverse_wire(wires[0],i)
w2,nsteps2= traverse_wire(wires[1],j)
ints = get_intersections(w1,w2)
true_ints=[ints[r][1] for r in range(len(ints)) if ints[r][0]==True]
if len(true_ints)>0:
print(true_ints)
|
# This file will draw all bounding boxes picked up by the frontal_face classifier using your webcam.
# It will draw the average bounding box in red if multiple are clustered close enoughtogether.
import numpy as np
import cv2
# Global Varibules
res = [1280, 720] # Recording resolution
eps = 1.5 # Used in groupRectangles (line 38)
MIN_LENGTH = min(res) / 15.0 # This is if you would like to set a minimum length for the width of the bbox
classifierPath = '/Users/jeremy.meyer/opencv/data/haarcascades/haarcascade_frontalface_default.xml' # Stored locally
face_cascade = cv2.CascadeClassifier(classifierPath)
cap = cv2.VideoCapture(0) # 0 For Webcam
cap.set(3, res[0]) # Setting resolution
cap.set(4, res[1])
# Draws bounding box and text from coordinates with a given (x1, y1, x2, y2). Can change displayed text
def bbox(img, x1, y1, x2, y2, base_color=(255, 0, 0), text='Human Detected'):
x_adj = 12*len(text) # Length of dark rectangle behind text. Adjusts for longer/shorter texts
y_adj = 17
cv2.rectangle(img, (x1, y1), (x2, y2), base_color, 2)
if y1 > 20:
cv2.rectangle(img, (x1, y1 - y_adj), (x1 + x_adj, y1 - 1), np.array(base_color) / 5, -1)
cv2.putText(img, text, (x1, y1 - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, base_color)
else: # This is if the bbox is towards the top of the screen
cv2.rectangle(img, (x1, y2 + y_adj), (x1 + x_adj, y2 + 1), np.array(base_color) / 5, -1)
cv2.putText(img, text, (x1, y2 + y_adj - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, base_color)
while True:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Convert to grayscale for simpler calculations
faces = face_cascade.detectMultiScale(gray) # Detected faces
grouped = cv2.groupRectangles(list(faces), 1, eps=eps) # Rectangles that were the result of clustering
# Draws bboxes on original calculated faces in blue
for (x, y, w, h) in faces:
if w > MIN_LENGTH:
bbox(img, x, y, x + w, y + h, (255, 175, 0))
# Draws bboxes on cluster-combined rectangles in red
for (x, y, w, h) in grouped[0]:
if w > MIN_LENGTH:
bbox(img, x, y, x + w, y + h, (0, 0, 255), "Human (Averaged)")
# Shows the frame. Hit ESC to close out.
cv2.imshow('img', img)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
|
#!/usr/bin/env python
import pika
import iptc
connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.20.10'))
channel = connection.channel()
channel.exchange_declare(exchange='ip', type='fanout')
result = channel.queue_declare(exclusive=True)
queue_name = result.method.queue
channel.queue_bind(exchange='ip', queue=queue_name)
print ' [*] Waiting for ip. To exit press CTRL+C'
def deny_ip(body):
chain = iptc.Chain(iptc.Table(iptc.Table.FILTER), "INPUT")
rule = iptc.Rule()
rule.in_interface = "eth+"
rule.src = "%r/255.255.255.0" % body
target = iptc.Target(rule, "DROP")
rule.target = target
chain.insert_rule(rule)
def callback(ch, method, properties, body):
deny_ip(body)
print " [x] Drop: %r" % (body,)
channel.basic_consume(callback, queue=queue_name, no_ack=True)
channel.start_consuming()
|
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.metrics import plot_confusion_matrix
from mnist import MNIST
import gzip
import numpy as np
import matplotlib.pyplot as plt
mndata = MNIST('data')
np.set_printoptions(precision=2, suppress=True)
X_train, y_train = mndata.load_training()
X_test, y_test = mndata.load_testing()
X_train, y_train = np.array(X_train)/255, np.array(y_train)
X_test, y_test = np.array(X_test)/255, np.array(y_test)
clf = MLPClassifier(solver='sgd', alpha=1e-5, hidden_layer_sizes=(5, 3), random_state=1)
pred = clf.fit(X_train, y_train).predict(X_test)
print("Logistic Regression accuracy: ", accuracy_score(y_test, pred, normalize=True))
labels = [x for x in range(10)]
disp = plot_confusion_matrix(clf, X_test, y_test, display_labels=labels, cmap=plt.cm.Blues, normalize="true")
disp.ax_.set_title("chorro")
print("Confusion matrix:\n%s" % disp.confusion_matrix)
plt.show()
|
from flask import Flask, render_template
import pandas as pd
import requests
from bs4 import BeautifulSoup
from io import BytesIO
import base64
import matplotlib.pyplot as plt
app = Flask(__name__)
def scrap(url):
#This is fuction for scrapping
url_get = requests.get(url)
soup = BeautifulSoup(url_get.content,"html.parser")
#Find the key to get the information
table = soup.find('div', attrs={'class':'lister list detail sub-list'})
rowDiv = table.find_all('div',attrs={'class':'lister-item mode-advanced'})
temp = [] #initiating a tuple
for i in range(0, len(rowDiv)):
#get title
title = rowDiv[i].find('h3',attrs={'class':'lister-item-header'}).find('a').text
title = title.strip() #for removing the excess whitespace
#get rating
rating = rowDiv[i].find('div',attrs={'class':'inline-block ratings-imdb-rating'}).text
rating = rating.strip() #for removing the excess whitespace
#get meta score
if(rowDiv[i].find('span',attrs={'class':'metascore favorable'})) is None:
metascore = '0'
else:
metascore = rowDiv[i].find('span',attrs={'class':'metascore favorable'}).text
metascore = metascore.strip()
#votes
votes = rowDiv[i].find('span',attrs={'name':'nv'}).text
votes = votes.strip()
temp.append((title,rating,metascore,votes))
temp = temp[::-1] #remove the header
df = pd.DataFrame(temp, columns= (('title','rating','metascore','votes')))
#df = pd.DataFrame(temp, columns = (('title','rating','metascore','votes')) #creating the dataframe
#data wranggling - try to change the data type to right data type
df['rating'] = df['rating'].astype('float')
df['metascore'] = df['metascore'].astype('float')
df['title'] = df['title'].astype('category')
df['votes'] = df['votes'].str.replace(',', '')
df['votes'] = df['votes'].astype('int')
#end of data wranggling
return df
@app.route("/")
def index():
df = scrap('https://www.imdb.com/search/title/?release_date=2019-01-01,2019-12-31') #insert url here
#This part for rendering matplotlib
fig = plt.figure(figsize=(5,2),dpi=300)
df.plot()
#Do not change this part
plt.savefig('plot1',bbox_inches="tight")
figfile = BytesIO()
plt.savefig(figfile, format='png')
figfile.seek(0)
figdata_png = base64.b64encode(figfile.getvalue())
result = str(figdata_png)[2:-1]
#This part for rendering matplotlib
#this is for rendering the table
df = df.to_html(classes=["table table-bordered table-striped table-dark table-condensed"])
return render_template("index.html", table=df, result=result)
if __name__ == "__main__":
app.run()
|
'''
A set of utilities to aid in easy and consistent playblasts
'''
from maya import cmds
import pymel.core as pm
import pymel.core.uitypes as pmui
import os
from maya import mel
import maya.OpenMayaAnim as oma
import glob
def clean_hud():
hud_menu = pm.melGlobals['gHeadsUpDisplayMenu']
menuitems = cmds.menu(hud_menu, q=True, itemArray=True)
class Playblaster(object):
"""
"""
# Default settings
override_vp=True
green = False
only_polygons = True
override_hud = True
display_hud = True
hud = True
scene_hud = True
camera_hud = True
custom_hud_chk = False
hud_frame_chk = True
custom_hud_text = ""
w = 960
h = 540
modelPanel = ""
default_color = [0,1,0]
overwrite = False
view = True
offscreen = False
camera = ""
gates = False
usescenename_chk = True
pb_format = [0, "qt"]
encoding = "H.264"
quality = 70
scale = 100
custom_resolution = False
save_directory = ""
def __init__(self):
self.proj = self.get_project()
self.start, self.end = self.start_end()
self.filename = self.pb_filename()
self.load_option_vars()
if not self.save_directory:
self.save_directory = os.path.join(cmds.workspace(q=True, fn=True), "movies").replace("\\", "/")
def load_option_vars(self):
# check for preferences, and load them if they exist
if cmds.optionVar(exists="gp_overrideviewport_chk"):
self.override_vp = bool(cmds.optionVar(q="gp_overrideviewport_chk"))
if cmds.optionVar(exists="gp_onlypolygons_chk"):
self.only_polygons = bool(cmds.optionVar(q="gp_onlypolygons_chk"))
if cmds.optionVar(exists="gp_gates_chk"):
self.gates = bool(cmds.optionVar(q="gp_gates_chk"))
if cmds.optionVar(exists="gp_bgcolor_chk"):
self.green = bool(cmds.optionVar(q="gp_bgcolor_chk"))
if cmds.optionVar(exists="gp_bgcolorR"):
color =[]
color.append(cmds.optionVar(q="gp_bgcolorR"))
color.append(cmds.optionVar(q="gp_bgcolorG"))
color.append(cmds.optionVar(q="gp_bgcolorB"))
self.default_color = color
if cmds.optionVar(exists="gp_overridehud_chk"):
self.override_hud = bool(cmds.optionVar(q="gp_overridehud_chk"))
if cmds.optionVar(exists="gp_displayhud_chk"):
self.display_hud = bool(cmds.optionVar(q="gp_displayhud_chk"))
if cmds.optionVar(exists="gp_projecthud_chk"):
self.hud = bool(cmds.optionVar(q="gp_projecthud_chk"))
if cmds.optionVar(exists="gp_frameHud_chk"):
self.hud_frame_chk = bool(cmds.optionVar(q="gp_frameHud_chk"))
if cmds.optionVar(exists="gp_camerahud_chk"):
self.camera_hud = bool(cmds.optionVar(q="gp_camerahud_chk"))
if cmds.optionVar(exists="gp_scenehud_chk"):
self.scene_hud = bool(cmds.optionVar(q="gp_scenehud_chk"))
if cmds.optionVar(exists="gp_username_chk"):
self.custom_hud_chk = bool(cmds.optionVar(q="gp_username_chk"))
if cmds.optionVar(exists="gp_format_ind"):
self.pb_format[0] = int(cmds.optionVar(q="gp_format_ind"))
if cmds.optionVar(exists="gp_format_cmb"):
self.pb_format[1] = cmds.optionVar(q="gp_format_cmb")
if cmds.optionVar(exists="gp_encoding_cmb"):
self.encoding = cmds.optionVar(q="gp_encoding_cmb")
if cmds.optionVar(exists="gp_quality_le"):
self.quality = int(cmds.optionVar(q="gp_quality_le"))
if cmds.optionVar(exists="gp_customresolution_chk"):
self.custom_resolution = bool(cmds.optionVar(q="gp_customresolution_chk"))
if cmds.optionVar(exists="gp_height_le") and self.custom_resolution:
self.h = int(cmds.optionVar(q="gp_height_le"))
if cmds.optionVar(exists="gp_width_le") and self.custom_resolution:
self.w = int(cmds.optionVar(q="gp_width_le"))
if cmds.optionVar(exists="gp_scale_le"):
self.scale = float(cmds.optionVar(q="gp_scale_le"))
if cmds.optionVar(exists="gp_offscreen_chk"):
self.offscreen = bool(cmds.optionVar(q="gp_offscreen_chk"))
if cmds.optionVar(exists="gp_view_chk"):
self.view = bool(cmds.optionVar(q="gp_view_chk"))
if cmds.optionVar(exists="gp_overwrite_chk"):
self.overwrite = bool(cmds.optionVar(q="gp_overwrite_chk"))
if cmds.optionVar(exists="gp_usescenename_chk"):
self.usescenename_chk = bool(cmds.optionVar(q="gp_usescenename_chk"))
if cmds.optionVar(exists="gp_scenename_le") and not self.usescenename_chk:
self.filename = (cmds.optionVar(q="gp_scenename_le"))
if cmds.optionVar(exists="gp_savedir_le"):
self.save_directory = (cmds.optionVar(q="gp_savedir_le"))
def get_project(self):
projpath = cmds.workspace(q=True, sn=True)
proj = os.path.basename(projpath)
return proj
def scene_name_hud(self):
if cmds.headsUpDisplay("HUDSceneName", exists=True):
cmds.headsUpDisplay("HUDSceneName", remove=True)
scene = cmds.file(q=True, sn=True, shn=True)
cmds.headsUpDisplay("HUDSceneName", section=5, block=2, blockSize="small", dfs="small", l=scene)
def proj_name_hud(self):
if cmds.headsUpDisplay("HUDProjName", exists=True):
cmds.headsUpDisplay("HUDProjName", remove=True)
cmds.headsUpDisplay("HUDProjName", section=5, block=3, blockSize="small", dfs="small", l=self.proj)
def framecount_hud(self):
if cmds.headsUpDisplay("HUDFrameCount", exists=True):
cmds.headsUpDisplay("HUDFrameCount", remove=True)
cmds.headsUpDisplay("HUDFrameCount", section=5, block=1, blockSize="small", dfs="large", l="frame",
command="cmds.currentTime(q=True)", atr=True)
def custom_hud(self, text=""):
if cmds.headsUpDisplay("HUDCustom", exists=True):
cmds.headsUpDisplay("HUDCustom", remove=True)
cmds.headsUpDisplay("HUDCustom", section=5, block=4, blockSize="small", dfs="large", label=text)
def set_hud(self):
self.cameraNamesVisibility = cmds.optionVar(q="cameraNamesVisibility")
self.animationDetailsVisibility = cmds.optionVar(q="animationDetailsVisibility")
self.capsLockVisibility = cmds.optionVar(q="capsLockVisibility")
self.currentContainerVisibility = cmds.optionVar(q="currentContainerVisibility")
self.capsLockVisibility = cmds.optionVar(q="capsLockVisibility")
self.currentFrameVisibility = cmds.optionVar(q="currentFrameVisibility")
self.focalLengthVisibility = cmds.optionVar(q="focalLengthVisibility")
self.frameRateVisibility = cmds.optionVar(q="frameRateVisibility")
self.hikDetailsVisibility = cmds.optionVar(q="hikDetailsVisibility")
self.materialLoadingDetailsVisibility = cmds.optionVar(q="materialLoadingDetailsVisibility")
self.objectDetailsVisibility = cmds.optionVar(q="objectDetailsVisibility")
self.particleCountVisibility = cmds.optionVar(q="particleCountVisibility")
self.polyCountVisibility = cmds.optionVar(q="polyCountVisibility")
self.sceneTimecodeVisibility = cmds.optionVar(q="sceneTimecodeVisibility")
self.selectDetailsVisibility = cmds.optionVar(q="selectDetailsVisibility")
self.symmetryVisibility = cmds.optionVar(q="symmetryVisibility")
self.viewAxisVisibility = cmds.optionVar(q="viewAxisVisibility")
self.viewportRendererVisibility = cmds.optionVar(q="viewportRendererVisibility")
self.evaluationManagerHUDVisibility = cmds.optionVar(q="evaluationVisibility")
if cmds.pluginInfo("xgenToolkit", loaded=True, q=True):
self.xgenHUDVisibility = cmds.optionVar(q="xgenHUDVisibility")
self.originAxis = cmds.toggleAxis(o=True, q=True)
if not self.override_hud:
return
mel.eval('setCameraNamesVisibility(0);')
mel.eval('setAnimationDetailsVisibility(0)')
mel.eval('setCapsLockVisibility(0)')
mel.eval('setCurrentContainerVisibility(0)')
mel.eval('setCapsLockVisibility(0)')
mel.eval('setCurrentFrameVisibility(0)')
mel.eval('setFocalLengthVisibility(0)')
mel.eval('setFrameRateVisibility(0)')
mel.eval('setHikDetailsVisibility(0)')
mel.eval('ToggleMaterialLoadingDetailsHUDVisibility(0)')
mel.eval('setObjectDetailsVisibility(0)')
mel.eval('setParticleCountVisibility(0)')
mel.eval('setPolyCountVisibility(0)')
mel.eval('setSceneTimecodeVisibility(0)')
mel.eval('setSelectDetailsVisibility(0)')
mel.eval('setSymmetryVisibility(0)')
mel.eval('setViewAxisVisibility(0)')
mel.eval('setViewportRendererVisibility(0)')
mel.eval('SetEvaluationManagerHUDVisibility(0)')
mel.eval('viewManip - v(0);')
mel.eval('toggleAxis - o(0);')
if cmds.pluginInfo("xgenToolkit", loaded=True, q=True):
mel.eval('setXGenHUDVisibility(0)')
if not self.display_hud:
return
if self.hud:
self.proj_name_hud()
if self.scene_hud:
self.scene_name_hud()
if self.hud_frame_chk:
self.framecount_hud()
if self.custom_hud_chk:
self.custom_hud(self.custom_hud_text)
if self.camera_hud and self.override_hud:
cam = 1
else:
cam = 0
mel.eval('setCameraNamesVisibility(%s);' % cam)
def reset_hud(self):
if cmds.headsUpDisplay("HUDProjName", exists=True):
cmds.headsUpDisplay("HUDProjName", remove=True)
if cmds.headsUpDisplay("HUDSceneName", exists=True):
cmds.headsUpDisplay("HUDSceneName", remove=True)
if cmds.headsUpDisplay("HUDFrameCount", exists=True):
cmds.headsUpDisplay("HUDFrameCount", remove=True)
if cmds.headsUpDisplay("HUDCustom", exists=True):
cmds.headsUpDisplay("HUDCustom", remove=True)
mel.eval('setCameraNamesVisibility(%s);'% self.cameraNamesVisibility)
mel.eval('setAnimationDetailsVisibility(%s);'% self.animationDetailsVisibility)
mel.eval('setCapsLockVisibility(%s);'% self.capsLockVisibility)
mel.eval('setCurrentContainerVisibility(%s);'% self.currentContainerVisibility)
mel.eval('setCapsLockVisibility(%s);'% self.capsLockVisibility)
mel.eval('setCurrentFrameVisibility(%s);'% self.currentFrameVisibility)
mel.eval('setFocalLengthVisibility(%s);'% self.focalLengthVisibility)
mel.eval('setFrameRateVisibility(%s);'% self.frameRateVisibility)
mel.eval('setHikDetailsVisibility(%s);'% self.hikDetailsVisibility)
mel.eval('ToggleMaterialLoadingDetailsHUDVisibility(%s);'% self.materialLoadingDetailsVisibility)
mel.eval('setObjectDetailsVisibility(%s);'% self.objectDetailsVisibility)
mel.eval('setParticleCountVisibility(%s);'% self.particleCountVisibility)
mel.eval('setPolyCountVisibility(%s);'% self.polyCountVisibility)
mel.eval('setSceneTimecodeVisibility(%s);'% self.sceneTimecodeVisibility)
mel.eval('setSelectDetailsVisibility(%s);'% self.selectDetailsVisibility)
mel.eval('setSymmetryVisibility(%s);'% self.symmetryVisibility)
mel.eval('setViewAxisVisibility(%s);'% self.viewAxisVisibility)
mel.eval('setViewportRendererVisibility(%s);'% self.viewportRendererVisibility)
mel.eval('SetEvaluationManagerHUDVisibility(%s);'% self.evaluationManagerHUDVisibility)
cmds.toggleAxis(o=self.originAxis)
if cmds.pluginInfo("xgenToolkit", loaded=True, q=True):
mel.eval('setXGenHUDVisibility(%s);' % self.xgenHUDVisibility)
def get_active_viewport(self):
active_panel = pmui.ModelEditor(pm.getPanel(withFocus=True))
model_editor_list = pm.lsUI(editors=True)
for myModelPanel in model_editor_list:
if myModelPanel.find(active_panel) != -1:
model_editor = myModelPanel
if pm.getPanel(to=active_panel) == "modelPanel":
self.modelPanel = model_editor
#self.camera = (pm.modelEditor(self.modelPanel, q=True, camera=True)).getShape()
self.camera = (pm.modelEditor(self.modelPanel, q=True, camera=True))
if pm.nodeType(self.camera) == "transform":
self.camera = self.camera.getShape()
print pm.nodeType(self.camera)
return model_editor
else:
self.modelPanel = ""
pm.displayWarning("No viewport active.")
return None
def reset_viewports(self):
pmui.ModelEditor(self.modelPanel).setNurbsCurves(self.vp_curves)
pmui.ModelEditor(self.modelPanel).setNurbsSurfaces(self.vp_nurbs)
pmui.ModelEditor(self.modelPanel).setControlVertices(self.vp_cvs)
pmui.ModelEditor(self.modelPanel).setHulls(self.vp_hulls)
pmui.ModelEditor(self.modelPanel).setPolymeshes(self.vp_polys)
pmui.ModelEditor(self.modelPanel).setSubdivSurfaces(self.vp_subdivs)
pmui.ModelEditor(self.modelPanel).setPlanes(self.vp_planes)
pmui.ModelEditor(self.modelPanel).setLights(self.vp_lights)
pmui.ModelEditor(self.modelPanel).setCameras(self.vp_cameras)
pmui.ModelEditor(self.modelPanel).setImagePlane(self.vp_imageplanes)
pmui.ModelEditor(self.modelPanel).setJoints(self.vp_joints)
pmui.ModelEditor(self.modelPanel).setIkHandles(self.vp_iks)
pmui.ModelEditor(self.modelPanel).setDeformers(self.vp_deformers)
pmui.ModelEditor(self.modelPanel).setDynamics(self.vp_dynamics)
cmds.modelEditor(self.modelPanel, particleInstancers=self.vp_instancers, e=True)
pmui.ModelEditor(self.modelPanel).setFluids(self.vp_fluids)
pmui.ModelEditor(self.modelPanel).setHairSystems(self.vp_hair)
pmui.ModelEditor(self.modelPanel).setFollicles(self.vp_follicles)
pmui.ModelEditor(self.modelPanel).setNCloths(self.vp_nCloths)
pmui.ModelEditor(self.modelPanel).setNParticles(self.vp_nParticles)
pmui.ModelEditor(self.modelPanel).setNRigids(self.vp_nRigids)
pmui.ModelEditor(self.modelPanel).setDynamicConstraints(self.vp_dynconstraints)
pmui.ModelEditor(self.modelPanel).setLocators(self.vp_locators)
pmui.ModelEditor(self.modelPanel).setDimensions(self.vp_dimensions)
pmui.ModelEditor(self.modelPanel).setPivots(self.vp_pivots)
pmui.ModelEditor(self.modelPanel).setHandles(self.vp_handles)
pmui.ModelEditor(self.modelPanel).setTextures(self.vp_textureplacements)
pmui.ModelEditor(self.modelPanel).setStrokes(self.vp_strokes)
pmui.ModelEditor(self.modelPanel).setMotionTrails(self.vp_motiontrails)
cmds.modelEditor(self.modelPanel, clipGhosts=self.vp_clipghosts, e=True)
cmds.modelEditor(self.modelPanel, greasePencils=self.vp_greasepencil, e=True)
pmui.ModelEditor(self.modelPanel).setManipulators(self.vp_manipulators)
pmui.ModelEditor(self.modelPanel).setGrid(self.vp_grid)
pmui.ModelEditor(self.modelPanel).setHeadsUpDisplay(self.vp_hud)
cmds.modelEditor(self.modelPanel, hos=self.vp_holdouts, e=True)
pmui.ModelEditor(self.modelPanel).setSelectionHiliteDisplay(self.vp_selectionhighlighting)
def set_cameras(self):
if not self.override_vp:
return
self.cam_dr = self.camera.displayResolution.get()
self.cam_df = self.camera.displayFilmGate.get()
self.cam_dsa = self.camera.displaySafeAction.get()
self.cam_dst = self.camera.displaySafeTitle.get()
self.cam_overscan = self.camera.overscan.get()
if not self.gates:
self.camera.displayResolution.set(0)
self.camera.displayFilmGate.set(0)
self.camera.displaySafeAction.set(0)
self.camera.displaySafeTitle.set(0)
self.camera.overscan.set(1)
def reset_cameras(self):
self.camera.displayResolution.set(self.cam_dr)
self.camera.displayFilmGate.set(self.cam_df)
self.camera.displaySafeAction.set(self.cam_dsa)
self.camera.displaySafeTitle.set(self.cam_dst)
self.camera.overscan.set(self.cam_overscan)
def set_viewports(self):
if not self.override_vp:
return
self.get_veiwport_settings()
if self.only_polygons:
hrg = pm.PyNode("hardwareRenderingGlobals")
hrg.multiSampleEnable.set(1)
pmui.ModelEditor(self.modelPanel).setNurbsCurves(False)
pmui.ModelEditor(self.modelPanel).setNurbsSurfaces(False)
pmui.ModelEditor(self.modelPanel).setControlVertices(False)
pmui.ModelEditor(self.modelPanel).setHulls(False)
pmui.ModelEditor(self.modelPanel).setPolymeshes(True)
pmui.ModelEditor(self.modelPanel).setSubdivSurfaces(False)
pmui.ModelEditor(self.modelPanel).setPlanes(False)
pmui.ModelEditor(self.modelPanel).setLights(False)
pmui.ModelEditor(self.modelPanel).setCameras(False)
pmui.ModelEditor(self.modelPanel).setImagePlane(False)
pmui.ModelEditor(self.modelPanel).setJoints(False)
pmui.ModelEditor(self.modelPanel).setIkHandles(False)
pmui.ModelEditor(self.modelPanel).setDeformers(False)
pmui.ModelEditor(self.modelPanel).setDynamics(False)
cmds.modelEditor(self.modelPanel, particleInstancers=False, e=True)
pmui.ModelEditor(self.modelPanel).setFluids(False)
pmui.ModelEditor(self.modelPanel).setHairSystems(False)
pmui.ModelEditor(self.modelPanel).setFollicles(False)
pmui.ModelEditor(self.modelPanel).setNCloths(False)
pmui.ModelEditor(self.modelPanel).setNParticles(False)
pmui.ModelEditor(self.modelPanel).setNRigids(False)
pmui.ModelEditor(self.modelPanel).setDynamicConstraints(False)
pmui.ModelEditor(self.modelPanel).setLocators(False)
pmui.ModelEditor(self.modelPanel).setDimensions(False)
pmui.ModelEditor(self.modelPanel).setPivots(False)
pmui.ModelEditor(self.modelPanel).setHandles(False)
pmui.ModelEditor(self.modelPanel).setTextures(False)
pmui.ModelEditor(self.modelPanel).setStrokes(False)
pmui.ModelEditor(self.modelPanel).setMotionTrails(False)
#pmui.ModelEditor(self.modelPanel).pluginShapes(False)
cmds.modelEditor(self.modelPanel, clipGhosts=False, e=True)
cmds.modelEditor(self.modelPanel, greasePencils=False, e=True)
pmui.ModelEditor(self.modelPanel).setManipulators(False)
pmui.ModelEditor(self.modelPanel).setGrid(False)
pmui.ModelEditor(self.modelPanel).setHeadsUpDisplay(True)
cmds.modelEditor(self.modelPanel, hos=False, e=True)
pmui.ModelEditor(self.modelPanel).setSelectionHiliteDisplay(False)
def get_veiwport_settings(self):
# stores the pre-playblast viewport visilbity settings
self.vp_curves = pmui.ModelEditor(self.modelPanel).getNurbsCurves()
self.vp_nurbs = pmui.ModelEditor(self.modelPanel).getNurbsSurfaces()
self.vp_cvs = pmui.ModelEditor(self.modelPanel).getControlVertices()
self.vp_hulls = pmui.ModelEditor(self.modelPanel).getHulls()
self.vp_polys = pmui.ModelEditor(self.modelPanel).getPolymeshes()
self.vp_subdivs = pmui.ModelEditor(self.modelPanel).getSubdivSurfaces()
self.vp_planes = pmui.ModelEditor(self.modelPanel).getPlanes()
self.vp_lights = pmui.ModelEditor(self.modelPanel).getLights()
self.vp_cameras = pmui.ModelEditor(self.modelPanel).getCameras()
self.vp_imageplanes = pmui.ModelEditor(self.modelPanel).getImagePlane()
self.vp_joints = pmui.ModelEditor(self.modelPanel).getJoints()
self.vp_iks = pmui.ModelEditor(self.modelPanel).getIkHandles()
self.vp_deformers = pmui.ModelEditor(self.modelPanel).getDeformers()
self.vp_dynamics = pmui.ModelEditor(self.modelPanel).getDynamics()
self.vp_instancers = cmds.modelEditor(self.modelPanel, particleInstancers=True, q=True)
self.vp_fluids = pmui.ModelEditor(self.modelPanel).getFluids()
self.vp_hair = pmui.ModelEditor(self.modelPanel).getHairSystems()
self.vp_follicles = pmui.ModelEditor(self.modelPanel).getFollicles()
self.vp_nCloths = pmui.ModelEditor(self.modelPanel).getNCloths()
self.vp_nParticles = pmui.ModelEditor(self.modelPanel).getNParticles()
self.vp_nRigids = pmui.ModelEditor(self.modelPanel).getNRigids()
self.vp_dynconstraints = pmui.ModelEditor(self.modelPanel).getDynamicConstraints()
self.vp_locators = pmui.ModelEditor(self.modelPanel).getLocators()
self.vp_dimensions = pmui.ModelEditor(self.modelPanel).getDimensions()
self.vp_pivots = pmui.ModelEditor(self.modelPanel).getPivots()
self.vp_handles = pmui.ModelEditor(self.modelPanel).getHandles()
self.vp_textureplacements = pmui.ModelEditor(self.modelPanel).getTextures()
self.vp_strokes = pmui.ModelEditor(self.modelPanel).getStrokes()
self.vp_motiontrails = pmui.ModelEditor(self.modelPanel).getMotionTrails()
self.vp_pluginshapes = pmui.ModelEditor(self.modelPanel).pluginShapes()
self.vp_clipghosts = cmds.modelEditor(self.modelPanel, clipGhosts=True, q=True)
self.vp_greasepencil = cmds.modelEditor(self.modelPanel, greasePencils=True, q=True)
self.vp_gpucache = cmds.modelEditor(self.modelPanel, queryPluginObjects="gpuCacheDisplayFilter", q=True)
self.vp_manipulators = pmui.ModelEditor(self.modelPanel).getManipulators()
self.vp_grid = pmui.ModelEditor(self.modelPanel).getGrid()
self.vp_hud = pmui.ModelEditor(self.modelPanel).getHeadsUpDisplay()
self.vp_holdouts = cmds.modelEditor(self.modelPanel, hos=True, q=True)
self.vp_selectionhighlighting = pmui.ModelEditor(self.modelPanel).getSelectionHiliteDisplay()
def render_resolution(self):
w = str(cmds.getAttr("defaultResolution.width"))
h = str(cmds.getAttr("defaultResolution.height"))
return w, h
def render_frameRange(self):
s = str(int(cmds.getAttr("defaultRenderGlobals.startFrame")))
e = str(int(cmds.getAttr("defaultRenderGlobals.endFrame")))
return s, e
def pb_filename(self):
# get the current scene name, remove the extension, and account for a scene without a name
mayafile = cmds.file(q=True, sn=True, shn=True)
if not mayafile:
mayafile = "untitled"
splitname = os.path.splitext(mayafile)
self.filename = splitname[0]
return self.filename
def start_end(self):
# get the selected timeline range, if it exists, otherwise use the visible timeline range
slider = pm.melGlobals['gPlayBackSlider']
if cmds.timeControl(slider, rangeVisible=True, q=True):
range = cmds.timeControl(slider, range=True, q=True)
s, e = range.split(":")
self.start = s[1:]
self.end = e[:-1]
else:
self.start = int(oma.MAnimControl.minTime().value())
self.end = int(oma.MAnimControl.maxTime().value())
return self.start, self.end
def playblast(self):
self.get_active_viewport()
if not self.modelPanel:
return
self.filename = os.path.join(self.save_directory, self.filename)
if not self.overwrite:
# glob allows searching for the filename with a wildcard for the extension
if glob.glob('%s.*' % self.filename):
if cmds.file(modified=True, q=True):
overwrite = cmds.confirmDialog(title="Playblasts Exists",
message="Overwrite Existing Playblast?",
button=["Overwrite", "Cancel"],
defaultButton="Overwrite",
cancelButton="Cancel",
dismissString="Cancel")
if not overwrite == "Overwrite":
cmds.warning("Action canceled")
return
# save the viewport settings so we can revert them later
self.get_veiwport_settings()
# set everything up for playblast
self.set_viewports()
self.set_cameras()
self.set_hud()
if self.green and self.override_vp:
r, g, b = cmds.displayRGBColor("background", q=True)
rt, gt, bt = cmds.displayRGBColor("backgroundTop", q=True)
rb, gb, bb = cmds.displayRGBColor("backgroundBottom", q=True)
cmds.displayRGBColor("background", *self.default_color)
cmds.displayRGBColor("backgroundTop", *self.default_color)
cmds.displayRGBColor("backgroundBottom", *self.default_color)
# Get active audio clip
gPlayBackSlider = pm.melGlobals['gPlayBackSlider']
audio = cmds.timeControl(gPlayBackSlider, q=True, sound=True)
# Do Playblast
cmds.playblast(
format=self.pb_format[1],
filename=self.filename,
sequenceTime=False,
clearCache=True,
viewer=self.view,
showOrnaments=True,
offScreen=self.offscreen,
compression=self.encoding,
quality=self.quality,
widthHeight=[self.w, self.h],
st=self.start,
et=self.end,
percent=(self.scale),
fo=True,
sound=audio
)
# Reset everything
self.reset_viewports()
self.reset_cameras()
if self.green and self.override_vp:
cmds.displayRGBColor("background", r, g, b)
cmds.displayRGBColor("backgroundTop", rt, gt, bt)
cmds.displayRGBColor("backgroundBottom", rb, gb, bb)
self.reset_hud()
return self.filename
|
#!/usr/bin/env python
"""
Implementation of the conversion from infix
to postfix notation using a stack.
"""
from pythonds.basic.stack import Stack
def convert(expression: str) -> str:
expression = list(expression)
output = []
opstack = Stack()
precedence = {"(": 1, "-": 2, "+": 2, "/": 3, "*": 3}
for token in expression:
if token in "ABCD":
output.append(token)
elif token == "(":
opstack.push(token)
elif token == ")":
topElement = opstack.pop()
while topElement != "(":
output.append(topElement)
topElement = opstack.pop()
elif token in precedence:
lowerPrec = False
while opstack.size() > 1 and not lowerPrec:
if (
opstack.peek() in precedence
and precedence[opstack.peek()] >= precedence[token]
):
output.append(opstack.pop())
else:
lowerPrec = True
opstack.push(token)
while not opstack.isEmpty():
output.append(opstack.pop())
return " ".join(output)
def main():
print(convert("(A+B)*(C+D)"))
if __name__ == "__main__":
main()
|
'''
Created on Jul 5, 2011
:authors: Gary belvin
'''
from charm.toolbox.conversion import Conversion
import unittest
class ConversionTest(unittest.TestCase):
def testOS2IP(self):
#9,202,000 = (0x)8c 69 50.
i = Conversion.OS2IP(b'\x8c\x69\x50')
self.assertEqual(i, 9202000)
def testIP2OS(self):
#9,202,000 = (0x)8c 69 50.
os = Conversion.IP2OS(9202000)
self.assertEqual(os, b'\x8c\x69\x50')
def testIP2OSLen(self):
i = 9202000
os = Conversion.IP2OS(i, 200)
i2 = Conversion.OS2IP(os)
self.assertEqual(i, i2)
if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testOS2IP']
unittest.main()
|
#!/usr/bin/env python3
import re
import sys
def main(filename):
with open(filename) as rd:
raw, mine, near = rd.read().split("\n\n")
my_ticket = [int(x) for x in mine.splitlines()[-1].split(",")]
nearby = [[int(y) for y in x.split(",")] for x in near.splitlines()[1:]]
parsed = re.findall(r'(.+): (\d+)-(\d+) or (\d+)-(\d+)', raw)
rules = {name: rule(ranges) for name, *ranges in parsed}
invalid = 0
valid_tickets = [my_ticket]
for t in nearby:
i = invalid_nums(t, rules)
if i is None:
valid_tickets.append(t)
else:
invalid += i
print("1: ", invalid)
matches = {name: get_match(rule, valid_tickets)
for name, rule in rules.items()}
previous = set()
s2 = 1
for name, cols in sorted(matches.items(), key=lambda x: len(x[1])):
if name.startswith("departure"):
s2 *= my_ticket[next(iter(cols - previous))]
previous = cols
print("2: ", s2)
def invalid_nums(t, rules):
for v in t:
if not any(rule(v) for rule in rules.values()):
return v
return None
def rule(line):
m1, n1, m2, n2 = map(int, line)
def r(n):
return m1 <= n <= n1 or m2 <= n <= n2
return r
def get_match(rule, valid_tickets):
return set.intersection(
*({idx for idx, value in enumerate(valid) if rule(value)}
for valid in valid_tickets)
)
if __name__ == "__main__":
if len(sys.argv) < 2:
print("ASJDKHSADL:FSD")
sys.exit(1)
main(sys.argv[1])
|
#!/usr/bin/env python
# Copyright (c) 2012 Google Inc. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""
Test cases when multiple targets in different directories have the same name.
"""
import TestGyp
test = TestGyp.TestGyp(formats=['ninja', 'make'])
# xcode-ninja fails to generate a project due to id collisions
# cf. https://code.google.com/p/gyp/issues/detail?id=461
if test.format == 'xcode-ninja':
test.skip_test()
test.run_gyp('subdirs.gyp', chdir='src')
test.relocate('src', 'relocate/src')
# Test that we build all targets.
test.build('subdirs.gyp', 'target', chdir='relocate/src')
test.must_exist('relocate/src/subdir1/action1.txt')
test.must_exist('relocate/src/subdir2/action2.txt')
# Test that we build all targets using the correct actions, even if they have
# the same names.
test.build('subdirs.gyp', 'target_same_action_name', chdir='relocate/src')
test.must_exist('relocate/src/subdir1/action.txt')
test.must_exist('relocate/src/subdir2/action.txt')
# Test that we build all targets using the correct rules, even if they have
# the same names.
test.build('subdirs.gyp', 'target_same_rule_name', chdir='relocate/src')
test.must_exist('relocate/src/subdir1/rule.txt')
test.must_exist('relocate/src/subdir2/rule.txt')
test.pass_test()
|
class Inside(): pass
class Outside(): pass
class Header(): pass
class NoHeader(): pass
def check(x):
a = x[0]
b = x[1]
#print(a)
#print(b)
assert(type(b) == int)
assert(b >= 0)
if isinstance(a, Header):
if b == 0:
exit("error 4")
else:
return(a, b)
elif isinstance(a, NoHeader):
if b == 0:
return (a, b)
else:
exit("error 2")
else:
exit("error 3")
def switch(s):
if isinstance(s, Outside):
return Inside()
elif isinstance(s, Inside):
return Outside()
def all_chars(x):
for i in x:
assert(type(i) == str)
assert(len(i) == 1)
def all_printable(x):
for i in x:
assert(i.isprintable())
def parse_csv(x, separators, escape_chars, header_num):
print(header_num)
assert(type(separators) == set)
assert(type(escape_chars) == set)
all_chars(separators)
all_chars(escape_chars)
assert(separators.intersection(escape_chars) == set())
assert(not ('\n' in separators))
assert(not ('\n' in escape_chars))
all_printable(separators)
all_printable(escape_chars)
check(header_num)
header_num = header_num[1]
x = open(x).read()
lines = [l for l in x.split('\n') if l.strip() != ""]
if header_num == 0:
headers = []
else:
headers = lines[:header_num]
content = lines[header_num:]
del lines
#print(headers)
#print(content)
headers = [separate(line, separators, escape_chars) for line in headers]
content = [separate(line, separators, escape_chars) for line in content]
#for token in content:
# assert(len(token) == len(headers))
return (headers, content)
def separate(line, separators, escape_chars):
state = Outside()
tokens = []
aux = ""
for c in line:
if c in escape_chars:
state = switch(state)
elif c in separators:
if isinstance(state, Inside):
aux += c
elif isinstance(state, Outside):
tokens.append(aux)
aux = ""
else:
exit("error")
else:
aux += c
tokens.append(aux)
return tokens
def reduce_repeated(x):
assert(type(x) == list)
last = None
answer = []
for i in x:
code = i[0]
names = i[1]
if code != last:
answer.append((code, names))
last = code
return answer
def from_some_weird_tuple_thing_to_csv(data, filename):
f = open(filename, 'w')
print("code, ingredient_group, real_product", file = f)
for d in data:
print(d[0] + "," + d[1] + "," + d[2], file = f)
f.close()
if __name__ == "__main__":
headers, content = parse_csv("central/Ingredient Nutrient Values-Table 1.csv", set([',']), set(['"']), (Header(), 4))
#print(content)
ans = []
for ingredient in content:
code = ingredient[0].strip().lower()
name = ingredient[1].strip().lower()
names = [n.strip() for n in name.split(',')]
ans.append((code, names))
#print(ans)
del ingredient
del content
del names
del name
del code
ans = reduce_repeated(ans)
#print(ans)
f = open("combined_searches_reduced.txt").read()
ingredients = [line for line in f.split('\n') if line.strip() != ""]
ingredients = [line.strip().lower() for line in ingredients]
ingredients = set(ingredients)
final = []
for ingredient in ingredients:
for code, keys in ans:
if ingredient in set(keys):
final.append((code, ingredient, "%".join(keys)))
print(final)
from_some_weird_tuple_thing_to_csv(final, "the_final_list_to_choose_from.csv")
|
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