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I was able to find somewhat of an answer to my question, but it was not as nested as my dictionary and so I am really unsure how to proceed as I am still very new to python. I currently have a nested dictionary like
{'140.10': {'46': {'1': '-49.50918', '2': '-50.223637', '3': '49.824406'}, '28': {'1': '-49.50918', '2': '-50.223637', '3': '49.824406'}}}:
I am wanting to plot it so that '140.10' becomes the title of the graph and '46' and '28' become the individual lines and key '1' for example is on the y axis and the x axis is the final number (in this case '-49.50918). Essentially a graph like this:
I generated this graph with a csv file that is written at another part of the code just with excel:
[![enter image description here][2]][2]
The problem I am running into is that these keys are autogenerated from a larger csv file and I will not know their exact value until the code has been run. As each of the keys are autogenerated in an earlier part of the script. As I will be running it over various files called the Graph name, and each file will have a different values for:
{key1:{key2_1: {key3_1: value1, key3_2: value2, key3_3: value3}, key_2_2 ...}}}
I have tried to do something like this:
for filename in os.listdir(Directory):
if filename.endswith('.csv'):
q = filename.split('.csv')[0]
s = q.split('_')[0]
if s in time_an_dict:
atom = list(time_an_dict[s])
ion = time_an_dict[s]
for f in time_an_dict[s]:
x_val = []
y_val = []
fz = ion[f]
for i in time_an_dict[s][f]:
pos = (fz[i])
frame = i
y_val.append(frame)
x_val.append(pos)
'''ions = atom
frame = frames
position = pos
plt.plot(frame, position, label = frames)
plt.xlabel("Frame")
plt.ylabel("Position")
plt.show()
#plt.savefig('{}_Pos.png'.format(s))'''
But it has not run as intended.
I have also tried:
for filename in os.listdir(Directory):
if filename.endswith('_Atom.csv'):
q = filename.split('.csv')[0]
s = q.split('_')[0]
if s in window_dict:
name = s + '_Atom.csv'
time_an_dict[s] = analyze_time(name,window_dict[s])
new = '{}_A_pos.csv'.format(s)
ions = list(time_an_dict.values())[0].keys()
for i in ions:
x_axis_values = []
y_axis_values = []
frame = list(time_an_dict[s][i])
x_axis_values.append(frame)
empty = []
print(x_axis_values)
for x in frame:
values = time_an_dict[s][i][x]
empty.append(values)
y_axis_values.append(empty)
plt.plot(x_axis_values, y_axis_values, label = x )
plt.show()
But keep getting the error:
Traceback (most recent call last): File "Atoms_pos.py", line 175, in
plt.plot(x_axis_values, y_axis_values, label = x ) File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/pyplot.py",
line 2840, in plot
return gca().plot( File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/axes/_axes.py",
line 1743, in plot
lines = [*self._get_lines(*args, data=data, **kwargs)] File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/axes/_base.py",
line 273, in call
yield from self._plot_args(this, kwargs) File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/axes/_base.py",
line 394, in _plot_args
self.axes.xaxis.update_units(x) File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/axis.py",
line 1466, in update_units
default = self.converter.default_units(data, self) File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/category.py",
line 107, in default_units
axis.set_units(UnitData(data)) File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/category.py",
line 176, in init
self.update(data) File "/Users/hxb51/opt/anaconda3/lib/python3.8/site-packages/matplotlib/category.py",
line 209, in update
for val in OrderedDict.fromkeys(data): TypeError: unhashable type: 'numpy.ndarray'
Here is the remainder of the other parts of the code that generate the files and dictionaries I am using. I was told in another question I asked that this could be helpful.
# importing dependencies
import math
import sys
import pandas as pd
import MDAnalysis as mda
import os
import numpy as np
import csv
import matplotlib.pyplot as plt
################################################################################
###############################################################################
Directory = '/Users/hxb51/Desktop/Q_prof/Displacement_Charge/Blah'
os.chdir(Directory)
################################################################################
''' We are only looking at the positions of the CLAs and SODs and not the DRUDE counterparts. We are assuming the DRUDE
are very close and it is not something that needs to be concerned with'''
def Positions(dcd, topo):
fields = ['Window', 'ION', 'ResID', 'Location', 'Position', 'Frame', 'Final']
with open('{}_Atoms.csv'.format(s), 'a') as d:
writer = csv.writer(d)
writer.writerow(fields)
d.close()
CLAs = u.select_atoms('segid IONS and name CLA')
SODs = u.select_atoms('segid IONS and name SOD')
CLA_res = len(CLAs)
SOD_res = len(SODs)
frame = 0
for ts in u.trajectory[-10:]:
frame +=1
CLA_pos = CLAs.positions[:,2]
SOD_pos = SODs.positions[:,2]
for i in range(CLA_res):
ids = i + 46
if CLA_pos[i] < 0:
with open('{}_Atoms.csv'.format(s), 'a') as q:
new_line = [s,'CLA', ids, 'Bottom', CLA_pos[i], frame,10]
writes = csv.writer(q)
writes.writerow(new_line)
q.close()
else:
with open('{}_Atoms.csv'.format(s), 'a') as q:
new_line = [s,'CLA', ids, 'Top', CLA_pos[i], frame, 10]
writes = csv.writer(q)
writes.writerow(new_line)
q.close()
for i in range(SOD_res):
ids = i
if SOD_pos[i] < 0:
with open('{}_Atoms.csv'.format(s), 'a') as q:
new_line = [s,'SOD', ids, 'Bottom', SOD_pos[i], frame,10]
writes = csv.writer(q)
writes.writerow(new_line)
q.close()
else:
with open('{}_Atoms.csv'.format(s), 'a') as q:
new_line = [s,'SOD', ids, 'Top', SOD_pos[i], frame, 10]
writes = csv.writer(q)
writes.writerow(new_line)
q.close()
csv_Data = pd.read_csv('{}_Atoms.csv'.format(s))
filename = s + '_Atom.csv'
sorted_df = csv_Data.sort_values(["ION", "ResID", "Frame"],
ascending=[True, True, True])
sorted_df.to_csv(filename, index = False)
os.remove('{}_Atoms.csv'.format(s))
''' this function underneath looks at the ResIds, compares them to make sure they are the same and then counts how many
times the ion flip flops around the boundaries'''
def turn_dict(f):
read = open(f)
reader = csv.reader(read, delimiter=",", quotechar = '"')
my_dict = {}
new_list = []
for row in reader:
new_list.append(row)
for i in range(len(new_list[:])):
prev = i - 1
if new_list[i][2] == new_list[prev][2]:
if new_list[i][3] != new_list[prev][3]:
if new_list[i][2] in my_dict:
my_dict[new_list[i][2]] += 1
else:
my_dict[new_list[i][2]] = 1
return my_dict
def plot_flips(f):
dict = turn_dict(f)
ions = list(dict.keys())
occ = list(dict.values())
plt.bar(range(len(dict)), occ, tick_label = ions)
plt.title("{}".format(s))
plt.xlabel("Residue ID")
plt.ylabel("Boundary Crosses")
plt.savefig('{}_Flip.png'.format(s))
def analyze_time(f, dicts):
read = open(f)
reader = csv.reader(read, delimiter=",", quotechar='"')
new_list = []
keys = list(dicts.keys())
time_dict = {}
pos_matrix = {}
for row in reader:
new_list.append(row)
fields = ['ResID', 'Position', 'Frame']
with open('{}_A_pos.csv'.format(s), 'a') as k:
writer = csv.writer(k)
writer.writerow(fields)
k.close()
for i in range(len(new_list[:])):
if new_list[i][2] in keys:
with open('{}_A_pos.csv'.format(s), 'a') as k:
new_line = [new_list[i][2], new_list[i][4], new_list[i][5]]
writes = csv.writer(k)
writes.writerow(new_line)
k.close()
read = open('{}_A_pos.csv'.format(s))
reader = csv.reader(read, delimiter=",", quotechar='"')
time_list = []
for row in reader:
time_list.append(row)
for j in range(len(keys)):
for i in range(len(time_list[1:])):
if time_list[i][0] == keys[j]:
pos_matrix[time_list[i][2]] = time_list[i][1]
time_dict[keys[j]] = pos_matrix
return time_dict
window_dict = {}
for filename in os.listdir(Directory):
s = filename.split('.dcd')[0]
fors = s + '.txt'
topos = '/Users/hxb51/Desktop/Q_prof/Displacement_Charge/topo.psf'
if filename.endswith('.dcd'):
print('We are starting with {} \n '.format(s))
u = mda.Universe(topos, filename)
Positions(filename, topos)
name = s + '_Atom.csv'
plot_flips(name)
window_dict[s] = turn_dict(name)
continue
time_an_dict = {}
for filename in os.listdir(Directory):
if filename.endswith('.csv'):
q = filename.split('.csv')[0]
s = q.split('_')[0]
if s in window_dict:
name = s + '_Atom.csv'
time_an_dict[s] = analyze_time(name,window_dict[s])
for filename in os.listdir(Directory):
if filename.endswith('.csv'):
q = filename.split('.csv')[0]
s = q.split('_')[0]
if s in time_an_dict:
atom = list(time_an_dict[s])
ion = time_an_dict[s]
for f in time_an_dict[s]:
x_val = []
y_val = []
fz = ion[f]
for i in time_an_dict[s][f]:
pos = (fz[i])
frame = i
y_val.append(frame)
x_val.append(pos)
'''ions = atom
frame = frames
position = pos
plt.plot(frame, position, label = frames)
plt.xlabel("Frame")
plt.ylabel("Position")
plt.show()
#plt.savefig('{}_Pos.png'.format(s))'''
Everything here runs well except this last bottom block of code. That deals with trying to make a graph from a nested dictionary. Any help would be appreciated!
Thanks!
I figured out the answer:
for filename in os.listdir(Directory):
if filename.endswith('_Atom.csv'):
q = filename.split('.csv')[0]
s = q.split('_')[0]
if s in window_dict:
name = s + '_Atom.csv'
time_an_dict[s] = analyze_time(name,window_dict[s])
new = '{}_A_pos.csv'.format(s)
ions = list(time_an_dict[s])
plt.yticks(np.arange(-50, 50, 5))
plt.xlabel('Frame')
plt.ylabel('Z axis position(Ang)')
plt.title([s])
for i in ions:
x_value = []
y_value = []
time_frame =len(time_an_dict[s][i]) +1
for frame in range(1,time_frame):
frame = str(frame)
x_value.append(int(frame))
y_value.append(float(time_an_dict[s][i][frame]))
plt.plot(x_value, y_value, label=[i])
plt.xticks(np.arange(1, 11, 1))
plt.legend()
plt.savefig('{}_Positions.png'.format(s))
plt.clf()
os.remove("{}_A_pos.csv".format(s))
From there, with the combo of the other parts of the code, it produces these graphs:
For more than 1 file as long as there is more '.dcd' files.
I have daily wind data from quickscat ftp://ftp.ifremer.fr/ifremer/cersat/products/gridded/mwf-quikscat/data/daily
The problem is zonal and meridional winds are two dimensional i.e. they contain only (lon, lat) as dimension not (time, lon,lat) as dimension. File contain all the information about time as variable and as dimension. I tried the copy all the dimension and variable data from input file to an output file but something goes wrong. It copy successfully lat, lon and time but does not copy the values of winds. In source file wind is 2-dimensional, but I want wind in output file as 3-dimensional with time as third dimension.Anyway time dimesion has length=1
import netCDF4 as nc
import numpy as np
import os
in_path = '2000'
out_path = '2000_new'
files = os.listdir(in_path)
fd=0
for names in files:
# print(names)
x_file = os.path.join(in_path,names)
y_file = os.path.join(out_path,names)
fd +=1
i_file = nc.Dataset(x_file, 'r')
z_w = i_file.variables['zonal_wind_speed'][:,:]
m_w = i_file.variables['meridional_wind_speed'][:,:]
y = i_file.variables['latitude'][:]
x = i_file.variables['longitude'][:]
t = i_file.variables['time'][:]
os.system("'rm y_file")
o_file = nc.Dataset(y_file, 'w', format='NETCDF4')
latitude = o_file.createDimension('latitude', y.size)
longitude = o_file.createDimension('longitude', x.size)
time = o_file.createDimension('time',None)
var = o_file.createVariable('latitude','f4',('latitude'), zlib=True)
o_file.variables['latitude'].units = 'degree_north'
o_file.variables['latitude'].long_name ='latitude'
o_file.variables['latitude'].axis = 'X'
var = o_file.createVariable('longitude','f4',('longitude'), zlib=True)
o_file.variables['longitude'].units = 'degree_east'
o_file.variables['longitude'].long_name = 'longitude'
o_file.variables['longitude'].axis = 'Y'
var = o_file.createVariable('time','d',('time'), zlib=True)
o_file.variables['time'].long_name = 'time'
o_file.variables['time'].units = "hours since 1900-1-1 0:0:0"
o_file.variables['time'].calendar = 'standard'
o_file.variables['time'].axis = 'T'
var = o_file.createVariable('u','f4',('time','latitude','longitude'),fill_value=-1.e+23, zlib=True)
o_file.variables['u'].long_name='zonal wind speed component'
o_file.variables['u'].units = 'meter second-1'
o_file.variables['u'].coordinates = 'longitude latitude'
o_file.variables['u'].time = 'time'
var = o_file.createVariable('v','f4',('time','latitude','longitude'),fill_value=-1.e+23, zlib = True)
o_file.variables['v'].long_name = 'meridional wind speed component'
o_file.variables['v'].units = 'meter second-1'
o_file.variables['v'].coordinates = 'longitude latitude'
o_file.variables['v'].time = 'time'
o_file.variables['latitude'][:] = y
o_file.variables['longitude'][:] =x
o_file.variables['time'][:] = t
o_file.variables['u'] = z_w
o_file.variables['v'] = m_w
i_file.close()
o_file.close()
Actually, your time dimension does not have length 1, it has unlimited length. If you actually want it to have length 1, you need to use
#time = o_file.createDimension('time',None)
time = o_file.createDimension('time',1)
instead.
Then, to set all data of the first (and only) time index to your values, use
o_file.variables['u'][0] = z_w
o_file.variables['v'][0] = m_w
If you do end up saving multiple times in the file, replace the 0 with the appropriate index for the data you are copying in.
Alternatively, because time dimension now has length 1, you could also copy it using numpy.expand_dims
o_file.variables['u'][:] = np.expand_dims(z_w, 0)
o_file.variables['v'][:] = np.expand_dims(m_w, 0)
I've gotten all the data I wanted from scraping this metacritc url (see below) however, I can't seem to put a value in for when I don't find the associated value for list (missing values)
I would like to have it so all the lists are even (so I can right to .csv)
Here is the code I have so far:
from requests import get
from bs4 import BeautifulSoup
from urllib.request import Request, urlopen
import pandas as pd
#Define year
year_number = 2018
# Define the URL
i = range(0, 1)
names = []
metascores = []
userscores = []
userscoresNew = []
release_dates = []
release_datesNew = []
publishers = []
ratings = []
genres = []
genresNew = []
for element in i:
url = "http://www.metacritic.com/browse/games/score/metascore/year/pc/filtered?view=detailed&sort=desc&year_selected=" + format(year_number)
print(url)
year_number -= 1
# not sure about this but it works (I was getting blocked by something and this the way I found around it)
req = Request(url, headers={'User-Agent': 'Mozilla/5.0'})
web_byte = urlopen(req).read()
webpage = web_byte.decode('utf-8')
#this grabs the all the text from the page
html_soup = BeautifulSoup(webpage, 'html5lib')
#this is for selecting all the games in from 1 to 100 (the list of them)
game_names = html_soup.find_all("div", class_="main_stats")
game_metas = html_soup.find_all("a", class_="basic_stat product_score")
game_users = html_soup.find_all("li", class_='stat product_avguserscore')
game_releases = html_soup.find_all("ul", class_='more_stats')
game_publishers = html_soup.find_all("li", class_='stat publisher')
game_ratings = html_soup.find_all("li", class_='stat maturity_rating')
game_genres = html_soup.find_all("li", class_='stat genre')
#Extract data from each game
for games in game_names:
name = games.find()
names.append(name.text.strip())
for games2 in game_metas:
metascore = games2.find()
metascores.append(metascore.text.strip())
for games3 in game_releases:
release_date = games3.find()
release_dates.append(release_date.text.strip())
for games4 in game_users:
userscore = games4.find('span', class_="data textscore textscore_favorable") or games4.find('span', class_="data textscore textscore_mixed")
if userscore:
userscores.append(userscore.text)
for games5 in game_publishers:
publisher = games5.find("span", class_ = "data")
if publisher:
publishers.append(publisher.text)
for games6 in game_ratings:
rating = games6.find("span", class_ = "data")
for games7 in game_genres:
genre = games7.find("span", class_ = "data")
if genre:
genres.append(genre.text)
for x in release_dates:
temp = str(x)
temp2 = temp.replace("Release Date:\n ", "")
release_datesNew.append(temp2)
for z in genres:
temp3 = str(z)
temp4 = temp3.strip()
temp5 = temp4.replace(" ", "")
genresNew.append(temp5)
df = pd.DataFrame({'Games:': names})
not sure how I would work that in to this code
From what I understand it's take all the data it can find but if there is a blank it doesn't know about it
can someone adivse the best solution for this situation
any help would be great
Thanks
Just add else's for the existing conditions...
if userscore:
userscores.append(userscore.text)
else:
userscores.append('na')
I cannot figure how to return all the items using this code:
#staticmethod
def create_dataset():
cols = Colleagues.get_all_colleagues()
cols_abs = ((col['Firstname'] + " " + col['Surname'], col['Absences']) for col in cols)
for col in cols_abs:
dataset = list()
sum_days = list()
for d in col[1]:
start_date = d[0]
end_date = d[1]
s = datetime.strptime(start_date, "%Y-%m-%d")
e = datetime.strptime(end_date, "%Y-%m-%d")
startdate = s.strftime("%b-%y")
days = numpy.busday_count(s, e) + 1
sum_days.append(days)
days_per_month = startdate, days
dataset.append(days_per_month)
dict_gen1 = dict(dataset)
comb_days = sum(sum_days)
dict_gen2 = {'Name': col[0], 'Spells': len(col[1]), 'Total(Days)': comb_days}
dict_comb = [{**dict_gen1, **dict_gen2}]
return dict_comb
It only returns the first "col". If I move the return statement outside of the loop it returns only the last item in my set of data. This is the output that is returned from col_abs:
('Jonny Briggs', [['2015-08-01', '2015-08-05'], ['2015-11-02', '2015-11-06'], ['2016-01-06', '2016-01-08'], ['2016-03-07', '2016-03-11']])
('Matt Monroe[['2015-12-08', '2015-12-11'], ['2016-05-23', '2016-05-26']])
('Marcia Jones', [['2016-02-02', '2016-02-04']])
('Pat Collins', [])
('Sofia Marowzich', [['2015-10-21', '2015-10-30'], ['2016-03-09', '2016-03-24']])
('Mickey Quinn', [['2016-06-06', '2016-06-08'], ['2016-01-18', '2016-01-21'], ['2016-07-21', '2016-07-22']])
('Jenifer Andersson', [])
('Jon Fletcher', [])
('James Gray', [['2016-04-01', '2016-04-06'], ['2016-07-04', '2016-07-07']])
('Matt Chambers', [['2016-05-02', '2016-05-04']])
Can anyone help me understand this better as I want to return a "dict_comb" for each entry in col_abs ?
Replace your return statement with a yield statement. This will allow your method to continue to loop while "yielding" or returning values after each iteration.
I’m working on a Python script that takes a set of input lines and assigns a mullion to the corresponding gridline that they intersect. However, I’m getting a strange error:
that I don’t know how to correct towards the end of the script. Python is telling me that it expected a MullionType and got a Family Type (see image). I’m using a modified version of Spring Nodes’ Collector.WallTypes that collects Mullion Types instead but the output of the node is a Family Type, which the script won’t accept. Any idea how to get the Mullion Type to feed into the final Python node?
SpringNodes script:
#Copyright(c) 2016, Dimitar Venkov
# #5devene, dimitar.ven#gmail.com
import clr
clr.AddReference("RevitServices")
import RevitServices
from RevitServices.Persistence import DocumentManager
doc = DocumentManager.Instance.CurrentDBDocument
clr.AddReference("RevitAPI")
from Autodesk.Revit.DB import *
clr.AddReference("RevitNodes")
import Revit
clr.ImportExtensions(Revit.Elements)
def tolist(obj1):
if hasattr(obj1,"__iter__"): return obj1
else: return [obj1]
fn = tolist(IN[0])
fn = [str(n) for n in fn]
result, similar, names = [], [], []
fec = FilteredElementCollector(doc).OfClass(MullionType)
for i in fec:
n1 = Element.Name.__get__(i)
names.append(n1)
if any(fn1 == n1 for fn1 in fn):
result.append(i.ToDSType(True))
elif any(fn1.lower() in n1.lower() for fn1 in fn):
similar.append(i.ToDSType(True))
if len(result) > 0:
OUT = result,similar
if len(result) == 0 and len(similar) > 0:
OUT = "No exact match found. Check partial below:",similar
if len(result) == 0 and len(similar) == 0:
OUT = "No match found! Check names below:", names
The SpringNodes script outputs a Family Type, even though the collector is for Mullion Types (see above image)
Here's my script:
import clr
# Import RevitAPI
clr.AddReference("RevitAPI")
import Autodesk
from Autodesk.Revit.DB import *
# Import DocumentManager and TransactionManager
clr.AddReference("RevitServices")
import RevitServices
from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
# Import ToDSType(bool) extension method
clr.AddReference("RevitNodes")
import Revit
clr.ImportExtensions(Revit.GeometryConversion)
from System import Array
clr.AddReference('ProtoGeometry')
from Autodesk.DesignScript.Geometry import *
import math
doc = DocumentManager.Instance.CurrentDBDocument
app = DocumentManager.Instance.CurrentUIApplication.Application
walls = UnwrapElement(IN[0])
toggle = IN[1]
inputLine = IN[2]
mullionType = IN[3]
wallSrf = []
heights = []
finalPoints = []
directions = []
isPrimary = []
projectedCrvs = []
keySegments = []
keySegmentsGeom = []
gridSegments = []
gridSegmentsGeom = []
gridLines = []
gridLinesGeom = []
keyGridLines = []
keyGridLinesGeom = []
projectedGridlines = []
lineDirections = []
gridLineDirection = []
allTrueFalse = []
if toggle == True:
TransactionManager.Instance.EnsureInTransaction(doc)
for w, g in zip(walls,inputLine):
pointCoords = []
primary = []
## Get curtain wall element sketch line
originLine = Revit.GeometryConversion.RevitToProtoCurve.ToProtoType( w.Location.Curve, True )
originLineLength = w.Location.Curve.ApproximateLength
## Get curtain wall element height, loft to create surface
for p in w.Parameters:
if p.Definition.Name == 'Unconnected Height':
height = p.AsDouble()
topLine = originLine.Translate(0,0,height)
srfCurves = [originLine,topLine]
wallSrf = NurbsSurface.ByLoft(srfCurves)
## Get centerpoint of curve, determine whether it extends across entire gridline
projectedCrvCenterpoint = []
for d in g:
lineDirection = d.Direction.Normalized()
lineDirections.append(lineDirection)
curveProject= d.PullOntoSurface(wallSrf)
if abs(lineDirection.Z) == 1:
if curveProject.Length >= height-.5:
primary.append(False)
else:
primary.append(True)
else:
if curveProject.Length >= originLineLength-.5:
primary.append(False)
else:
primary.append(True)
centerPoint = curveProject.PointAtParameter(0.5)
pointList = []
projectedCrvCenterpoint.append(centerPoint)
## Project centerpoint of curve onto wall surface
for h in [centerPoint]:
pointUnwrap = UnwrapElement(centerPoint)
pointList.append(pointUnwrap.X)
pointList.append(pointUnwrap.Y)
pointList.append(pointUnwrap.Z)
pointCoords.append(pointList)
finalPoints.append(pointCoords)
isPrimary.append(primary)
projectedCrvs.append(projectedCrvCenterpoint)
TransactionManager.Instance.TransactionTaskDone()
TransactionManager.Instance.EnsureInTransaction(doc)
##Gather all segments of gridline geometry
for wall in UnwrapElement(walls):
gridSegments2 = []
gridSegmentsGeom2 = []
gridLines1 = []
gridLinesGeom1 = []
for id1 in wall.CurtainGrid.GetVGridLineIds():
gridLinesGeom1.append(Revit.GeometryConversion.RevitToProtoCurve.ToProtoType(doc.GetElement(id1).FullCurve))
gridLines1.append(doc.GetElement(id1))
VgridSegments1 = []
VgridSegmentsGeom1 = []
for i in doc.GetElement(id1).AllSegmentCurves:
VgridSegments1.append(i)
VgridSegmentsGeom1.append(Revit.GeometryConversion.RevitToProtoCurve.ToProtoType(i,True))
gridSegments2.append(VgridSegments1)
gridSegmentsGeom2.append(VgridSegmentsGeom1)
for id2 in wall.CurtainGrid.GetUGridLineIds():
gridLinesGeom1.append(Revit.GeometryConversion.RevitToProtoCurve.ToProtoType(doc.GetElement(id2).FullCurve))
gridLines1.append(doc.GetElement(id2))
UgridSegments1 = []
UgridSegmentsGeom1 = []
for i in doc.GetElement(id2).AllSegmentCurves:
UgridSegments1.append(i)
UgridSegmentsGeom1.append(Revit.GeometryConversion.RevitToProtoCurve.ToProtoType(i,True))
gridSegments2.append(UgridSegments1)
gridSegmentsGeom2.append(UgridSegmentsGeom1)
gridSegments.append(gridSegments2)
gridSegmentsGeom.append(gridSegmentsGeom2)
gridLines.append(gridLines1)
gridLinesGeom.append(gridLinesGeom1)
boolFilter = [[[[b.DoesIntersect(x) for x in d] for d in z] for b in a] for a,z in zip(projectedCrvs, gridSegmentsGeom)]
boolFilter2 = [[[b.DoesIntersect(x) for x in z] for b in a] for a,z in zip(projectedCrvs, gridLinesGeom)]
##Select gridline segments that intersect with centerpoint of projected lines
for x,y in zip(boolFilter,gridSegments):
keySegments2 = []
keySegmentsGeom2 = []
for z in x:
keySegments1 = []
keySegmentsGeom1 = []
for g,l in zip(z,y):
for d,m in zip(g,l):
if d == True:
keySegments1.append(m)
keySegmentsGeom1.append(Revit.GeometryConversion.RevitToProtoCurve.ToProtoType(m,True))
keySegments2.append(keySegments1)
keySegmentsGeom2.append(keySegmentsGeom1)
keySegments.append(keySegments2)
keySegmentsGeom.append(keySegmentsGeom2)
##Order gridlines according to intersection with projected points
for x,y in zip(boolFilter2, gridLines):
keyGridLines1 = []
keyGridLinesGeom1 = []
for z in x:
for g,l in zip(z,y):
if g == True:
keyGridLines1.append(l)
keyGridLinesGeom1.append(Revit.GeometryConversion.RevitToProtoCurve.ToProtoType(l.FullCurve,True))
keyGridLines.append(keyGridLines1)
keyGridLinesGeom.append(keyGridLinesGeom1)
##Add mullions at intersected gridline segments
TransactionManager.Instance.TransactionTaskDone()
TransactionManager.Instance.EnsureInTransaction(doc)
for x,y,z in zip(keyGridLines,keySegments,isPrimary):
projectedGridlines1 = []
for h,j,k in zip(x,y,z):
for i in j:
if i != None:
h.AddMullions(i,mullionType,k)
projectedGridlines1.append(h)
projectedGridlines.append(projectedGridlines1)
else:
None
if toggle == True:
OUT = projectedGridlines
else:
None
TransactionManager.Instance.TransactionTaskDone()
Apologies for the messiness of the code, it's a modification of another node that I've been working on. Thanks for your help.
Bo,
Your problem is rooted in how Dynamo is wrapping elements to use with its own model. That last call .ToDSType(True) is the gist of the issue. MullionType class is a subclass (it inherits properties) from a ElementType class in Revit. When Dynamo team wraps that object into a custom wrapper they only wrote a top level wrapper that treats all ElementTypes the same, hence this outputs an ElementType/FamilyType rather than a specific MullionType.
First I would suggest that you replace the line of code in your code:
mullionType = IN[3]
with:
mullionType = UnwrapElement(IN[3])
This is their built in method for unwrapping elements to be used with calls to Revit API.
If that still somehow remains an issue, you could try and retrieve the MullionType object again, this time directly in your script, before you use it. You can do so like this:
for x,y,z in zip(keyGridLines,keySegments,isPrimary):
projectedGridlines1 = []
for h,j,k in zip(x,y,z):
for i in j:
if i != None:
h.AddMullions(i,doc.GetElement(mullionType.Id),k)
projectedGridlines1.append(h)
projectedGridlines.append(projectedGridlines1)
This should make sure that you get the MullionType element before it was wrapped.
Again, try unwrapping it first, then GetElement() call if first doesn't work.