Hello everyone, I have been trying to implement an already existing code to plot GTFS feed but getting attribute error somewhere in pandas module getting called inside from peartree module. I would be thankful for any help. Python --version -3.8 OS -- Windows 10 P.S. I have updated required modules still the problem persists.

Script:-

try: import peartree as pt except: pass import os import pickle PKL_PATH = 'graph.pkl' #Creating the graph takes a gazillion time so I pickle it if not os.path.exists(PKL_PATH): # Automatically identify the busiest day and # read that in as a Partidge feed feed = pt.get_representative_feed("F:\PhD\GTFS\GTFS_trial.zip") # Set a target time period to # use to summarize impedance start = 76060 # 7:00 AM end = 106060 # 10:00 AM # Converts feed subset into a directed # network multigraph G = pt.load_feed_as_graph(feed, start, end) with open(PKL_PATH, 'wb') as pkl_file: pickle.dump(G, pkl_file) else: with open(PKL_PATH, 'rb') as pkl_file: G = pickle.load(pkl_file)

Traceback (most recent call last): File "F:/PhD/Python/Directed_multigraph.py", line 31, in feed = pt.get_representative_feed("F:\PhD\GTFS\GTFS_trial.zip") File "C:\Anaconda3\envs\Python\lib\site-packages\peartree\paths.py", line 95, in get_representative_feed service_ids_by_date = ptg.read_service_ids_by_date(file_loc) File "C:\Anaconda3\envs\Python\lib\site-packages\partridge\readers.py", line 72, in read_service_ids_by_date return _service_ids_by_date(feed) File "C:\Anaconda3\envs\Python\lib\site-packages\partridge\readers.py", line 156, in _service_ids_by_date service_ids = set(feed.trips.service_id) File "C:\Anaconda3\envs\Python\lib\site-packages\pandas\core\generic.py", line 5274, in getattr return object.getattribute(self, name) AttributeError: 'DataFrame' object has no attribute 'service_id'

Hello,

I find myself facing an issue with the use of the G = pt.load_feed_as_graph(feed, start, end) command.

I am working with GTFS feed of the Paris region in France but I am not interested in the totality of the feed. As I only wanted to work on a smallest area, I selected the stop stations that were of interest to me and then extracted -into new GTFS files- the data of the original GTFS files that were linked to these stop stations. I used a script I found here that I modified a bit to fit my GTFS files and to trim them.

However, when I try to load my trimmed feed with G = pt.load_feed_as_graph(feed, start, end) I get the following error:

---------------------------------------------------------------------------
InsufficientSummaryResults                Traceback (most recent call last)
<ipython-input-119-74a13fcca0d5> in <module>
      3 # Converts feed subset into a directed network mugenerate_plotph
      4 
----> 5 G = pt.load_feed_as_graph(feed, start, end)
      6 
      7 end_time = time.time()

~/anaconda3/envs/iox/lib/python3.6/site-packages/peartree/paths.py in load_feed_as_graph(feed, start_time, end_time, name, existing_graph, connection_threshold, walk_speed_kmph, stop_cost_method, fallback_stop_cost, interpolate_times, impute_walk_transfers, use_multiprocessing)
    218                                                            interpolate_times,
    219                                                            stop_cost_method,
--> 220                                                            use_multiprocessing)
    221 
    222     # This is a flag used to check if we need to run any additional steps

~/anaconda3/envs/iox/lib/python3.6/site-packages/peartree/graph.py in generate_summary_graph_elements(feed, target_time_start, target_time_end, fallback_stop_cost, interpolate_times, stop_cost_method, use_multiprocessing)
    119 
    120     # Same sanity checks on the output before we continue
--> 121     _verify_outputs(all_edge_costs, all_wait_times)
    122 
    123     summary_edge_costs = generate_summary_edge_costs(all_edge_costs)

~/anaconda3/envs/iox/lib/python3.6/site-packages/peartree/graph.py in _verify_outputs(all_edge_costs, all_wait_times)
    208     # Handle if there are no valid edges returned (or wait times)
    209     if all_edge_costs is None or len(all_edge_costs) == 0:
--> 210         raise InsufficientSummaryResults('The target time frame returned no '
    211                                          'valid edge costs from feed object.')
    212     if all_wait_times is None or len(all_wait_times) == 0:

InsufficientSummaryResults: The target time frame returned no valid edge costs from feed object.

I don't understand why the error is raised, I think my GTFS files where trimmed properly so I should be able to create a graph with them.

Any help or indications would be greatly appreciated.

Hi, I am getting the above error when setting impute_walk_transfers to True in pt.load_feed_as_graph. I am able to construct the graph with just (feed, start, end), but unable to when including impute_walk_transfer. I want to incorporate bus to bus transfer and bus to subway transfer as well as walking edges in my network. Is this the right way to achieve that?

Per this tweet by GH user @rafapereirabr: A request to support graph-tool.

A Gist does exist to support graph-tool conversion from NetworkX.

Potential snafus would be increasing the complexity of the installation of this library by supporting graph-tool. One way around this would be to make the installation optional (akin to how GeoPandas treats Rtree).

I just upgraded to Pandas 1.2.0 on Python 3.8.5 and I am getting a warning from Pandas:

UserWarning: Boolean Series key will be reindexed to match DataFrame index.

At this line of code: https://github.com/kuanb/peartree/blob/254207ba759d82a1d66f84287075ce1f8d093463/peartree/parallel.py#L127

I think this is because the filter is using a different Dataframe from the Dataframe being filtered.

Using minimum of grouped edge weights effectively reduce path costs, and increase accessibility significantly. The following map shows shortest path lengths from one single source to all destinations in Berkeley. It changes from using original full network to coalesced network using min grouped edge weights. Noticing the shortest path lengths reduce significantly (darker color to lighter color)

The following map shows the same change but using coalesced network using mean (different color bins though). The change is less significant.

Also some stats comparison:

Stats | Full Network | Coalesced w Min | Coalesced w Mean --|--|--|-- Max shortest path length | 5172 | 3092 | 3493 Mean shortest path length | 2488 | 1383 | 1619

Visuals made by UrbanFootprint :))

Hello,

I am trying to using peartree to plot the GTFS data, but in the end I meet this error

UnboundLocalError`                         `Traceback` `(most` recent call last)
<ipython-input-12-3fede03b6b3a> in <module>
----> 1 pt.generate_plot(G)

~\Anaconda3\lib\site-packages\peartree\plot.py in generate_plot(G, use_agg)
     25     #       also plan on incorporating OSMnx into this library
     26     #       down the road so it isn't too extraneous an import.
---> 27     fig, ax = ox.plot_graph(G,
     28                             fig_height=12,
     29                             `show=False,`
UnboundLocalError: local variable 'ox' referenced before assignment

i have the following error, i´m using python 3.6.

KeyError Traceback (most recent call last) in () 1 from peartree.graph_tool import nx_to_gt 2 ----> 3 gtG = nx_to_gt(G.copy())

~/anaconda3/lib/python3.6/site-packages/peartree/graph_tool.py in nx_to_gt(nxG) 103 """ 104 # First, attempt to import graph-tool --> 105 gt = _import_graph_tool() 106 107 # Phase 0: Create a directed or undirected graph-tool Graph

~/anaconda3/lib/python3.6/site-packages/peartree/graph_tool.py in _import_graph_tool() 19 # If we fail to import it the first time, check to see if it 20 # has been downloaded in its default apt-get install directory ---> 21 sys.path.append(os.environ['GRAPH_TOOL_DIR']) 22 23 # Now retry with the new system path appended

~/anaconda3/lib/python3.6/os.py in getitem(self, key) 667 except KeyError: 668 # raise KeyError with the original key value --> 669 raise KeyError(key) from None 670 return self.decodevalue(value) 671

KeyError: 'GRAPH_TOOL_DIR'

I believe peartree 0.6.0 and partridge 1.0.0 are incompatible, although it seems to import correctly with partridge 0.11.0. The solution is to either include an explicit number reference to the partridge library on install, or identify the problem.

C:\WBG\anaconda3\envs\GOSTnet\lib\site-packages\peartree_init_.py in 

from peartree.version import version # noqa: F401
     from peartree.paths import (
load_feed_as_graph,
get_representative_feed,

C:\WBG\anaconda3\envs\GOSTnet\lib\site-packages\peartree\paths.py in 
import partridge as ptg
     from .graph import (generate_empty_md_graph, generate_summary_graph_elements,
make_synthetic_system_network, populate_graph)
from .synthetic import SyntheticTransitNetwork

C:\WBG\anaconda3\envs\GOSTnet\lib\site-packages\peartree\graph.py in 
from .settings import WGS84
    from .summarizer import (generate_edge_and_wait_values,
generate_summary_edge_costs, generate_summary_wait_times)

C:\WBG\anaconda3\envs\GOSTnet\lib\site-packages\peartree\summarizer.py in 
def generate_edge_and_wait_values(
    feed: ptg.feed,
    target_time_start: int,
    target_time_end: int,

AttributeError: module 'partridge' has no attribute 'feed'

Hi,

I have this kind of error after using import peartree as pt

  File "C:\anaconda2\lib\site-packages\peartree\parallel.py", line 18
    target_time_start: int,
                     ^
SyntaxError: invalid syntax

Looks like some very basic problem, but I'm not very well in python :)

Stop time interpolation works on the entire stop_times df, majority of which will be tossed later based on given requested time range.

Trimming down stop_times before passing it to the stop time interpolation step increases performance by a huge amount.

Here are some evidence of the performance gain on the pt.paths.generate_summary_graph_elements step:

gtfs id | current version | with trimming --|--|-- f-9q9-bart | 9.0s, 97 edges, 50 stops | 3.8s, 97 edges, 50 stops f-9q9-actransit | 132.0s, 5670 edges, 5050 stops | 59.8s, 5670 edges, 5050 stops f-9q8y-sfmta | 131.3s, 3806 edges, 3409 stops | 66.7s, 3806 edges, 3409 stops f-9qb-goldengatetransit | 10.6s, 519 edges, 473 stops | 7.5s, 519 edges, 473 stops f-9qc-fairfield~ca~us | 5.0s, 280 edges, 245 stops | 3.1s, 280 edges, 245 stops f-9qc0-soltrans~ca~us | 6.6s, 475 edges, 408 stops | 4.3s, 475 edges, 408 stops f-9qc-westcat~ca~us | 6.2s, 263 edges, 220 stops | 3.6s, 263 edges, 220 stops f-9-amtrak*** | 14.5s, 306 edges, 260 stops | 12.0s, 306 edges, 260 stops

The library generates the following error, spamming my terminal:

/home/user/.local/lib/python3.10/site-packages/peartree/graph.py:197: FutureWarning: iteritems is deprecated and will be removed in a future version. Use .items instead.

This PR fixes this.

There is a new ordering for axis in pyproj that requires +init=<auth>:<auth_code> to be replaced with <auth>:<auth_code>

Reference: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj

I was planning on using this library for something but it keeps giving me errors so I will try looking for others

I would like to have the option to add an attribute to graph edges that represents the number of trips that pass through an edge. This would be good for inspecting my GTFS data. I am making a pull request (#164) that adds this feature

Hello,

When I try to use the coalesce function on a path network from OSM the following error is raised:

KeyError                                  Traceback (most recent call last)
c:\Users\arqui\Documents\Repositorios\Identifying urban zones with spectral clustering\coalesse_poa.py in 
      81     # network_type='walk'
      82 )
----> 83 Gc = pt.toolkit.coalesce(G, 400)

~\anaconda3\envs\ox\lib\site-packages\peartree\toolkit.py in coalesce(G_orig, resolution, edge_summary_method, boarding_cost_summary_method)
    216     # such that we won't generate isolated nodes that become disconnected
    217     # from key coalesced nodes (because too many intermediary nodes)
--> 218     G = simplify_graph(G)
    219 
    220     # Extract all x, y values

~\anaconda3\envs\ox\lib\site-packages\peartree\toolkit.py in simplify_graph(G_orig)
    582         # If the path is not all one mode of travel, skip the
    583         # proposed simplification
--> 584         if not _path_has_consistent_mode_type(G, path):
    585             continue
    586 

~\anaconda3\envs\ox\lib\site-packages\peartree\toolkit.py in _path_has_consistent_mode_type(G, path)
    364         for i in range(edge_count):
    365             edge = G.edges[u, v, i]
--> 366             path_modes.append(edge['mode'])
    367     path_clear = all(x == path_modes[0] for x in path_modes)
    368     return path_clear

KeyError: 'mode'

Peartree version: 0.6.3 osmnx verson: 0.16.1

It's possible to use this function on a network without GTFS information?

Hi again @kuanb,

I continued digging around (see #124) and tested using the existing_graph -parameter to link walking and PT graphs together. I found that the stops around transit areas are connected together, but edges that would link stops to road network does not seem to work (as in the example below). Is this expected behavior?

The code that I used to produce the graph is:

G = pt.load_feed_as_graph(feed, start, end, 
                                 walk_speed_kmph=walk_speed,
                                 impute_walk_transfers=False,
                                 use_multiprocessing=True,
                                 existing_graph=walk_graph)