From 6f3405d7a40b92cfb4b796f4155038d16679e54a Mon Sep 17 00:00:00 2001
From: Lucas <lucas.heublein@t-online.de>
Date: Fri, 18 Aug 2023 17:33:55 +0200
Subject: [PATCH] Added a python file to connect to the seerver and run the
WBouncingScroll.
---
connect_to_mmt_WBounce.py | 204 ++++++++++++++++++++++++++++++++++++++
1 file changed, 204 insertions(+)
create mode 100644 connect_to_mmt_WBounce.py
diff --git a/connect_to_mmt_WBounce.py b/connect_to_mmt_WBounce.py
new file mode 100644
index 0000000..5e7d0c3
--- /dev/null
+++ b/connect_to_mmt_WBounce.py
@@ -0,0 +1,204 @@
+import http.client
+import json
+import time
+
+HOST = 'localhost' #'127.0.0.1'
+PORT = 8085
+headers = {'Content-type': 'application/json'}
+
+bouncing_scroll = 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll'
+X_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?xposition'}
+Y_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?yposition'}
+Xv_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?xvelocity'}
+Yv_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?yvelocity'}
+G_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?g_base'}
+B_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?bounce'}
+W_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?walls'}
+
+real_list = 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory2?real_list'
+list_type = 'http://gl.mathhub.info/MMT/LFX/Datatypes?ListSymbols?ListType'
+product = 'http://gl.mathhub.info/MMT/LFX/Sigma?Symbols?Product'
+real_lit = 'http://mathhub.info/MitM/Foundation?RealLiterals?real_lit'
+cons = 'http://gl.mathhub.info/MMT/LFX/Datatypes?ListSymbols?cons'
+cons_nil = 'http://gl.mathhub.info/MMT/LFX/Datatypes?ListSymbols?nil_constant'
+tuple_mmt = 'http://gl.mathhub.info/MMT/LFX/Sigma?Symbols?Tuple'
+
+
+def list_element_4tuple(x1, y1, x2, y2):
+ return {'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
+ 'arguments': [{'float': x1, 'kind': 'OMF'},
+ {'float': y1, 'kind': 'OMF'}],
+ 'kind': 'OMA'},
+ {'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
+ 'arguments': [{'float': x2, 'kind': 'OMF'},
+ {'float': y2, 'kind': 'OMF'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'}
+
+def list_element_4tuple_plus_nil(x1, y1, x2, y2):
+ return {'applicant': {'uri': cons, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': cons_nil, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
+ 'arguments': [{'uri': real_lit, 'kind': 'OMS'},
+ {'uri': real_lit, 'kind': 'OMS'}],
+ 'kind': 'OMA'},
+ {'applicant': {'uri': product, 'kind': 'OMS'},
+ 'arguments': [{'uri': real_lit, 'kind': 'OMS'},
+ {'uri': real_lit, 'kind': 'OMS'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'},
+ {'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
+ 'arguments': [{'float': x1, 'kind': 'OMF'},
+ {'float': y1, 'kind': 'OMF'}],
+ 'kind': 'OMA'},
+ {'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
+ 'arguments': [{'float': x2, 'kind': 'OMF'},
+ {'float': y2, 'kind': 'OMF'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'}
+
+def cons_2elements(e1, e2):
+ return {'applicant': {'uri': cons, 'kind': 'OMS'},
+ 'arguments': [e1, e2],
+ 'kind': 'OMA'}
+
+def construct_list_4tuple_df(values):
+ # Values needs to be of the form [[x1, y1, x2, y2], [x1, y1, x2, y2], ...]
+ prev_ele = {}
+ for ci, cv in enumerate(values[::-1]):
+ if ci == 0:
+ prev_ele = list_element_4tuple_plus_nil(cv[0], cv[1], cv[2], cv[3])
+ else:
+ cur_ele = list_element_4tuple(cv[0], cv[1], cv[2], cv[3])
+ prev_ele = cons_2elements(prev_ele, cur_ele)
+ return prev_ele
+
+def create_walls_fact(values):
+ # Values needs to be of the form [[x1, y1, x2, y2], [x1, y1, x2, y2], ...]
+ return {'ref': W_ref,
+ 'label': 'Walls',
+ 'tp': {'applicant': {'uri': list_type, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
+ 'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
+ 'arguments': [{'uri': real_lit, 'kind': 'OMS'},
+ {'uri': real_lit, 'kind': 'OMS'}],
+ 'kind': 'OMA'},
+ {'applicant': {'uri': product, 'kind': 'OMS'},
+ 'arguments': [{'uri': real_lit, 'kind': 'OMS'},
+ {'uri': real_lit, 'kind': 'OMS'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'}],
+ 'kind': 'OMA'},
+ 'kind': 'general',
+ 'df': construct_list_4tuple_df(values)
+ }
+
+def create_R_fact(val, ref):
+ return {"ref": ref,
+ "label": "X",
+ "kind": "general",
+ "tp": {'uri': 'http://mathhub.info/MitM/Foundation?RealLiterals?real_lit',
+ 'kind': 'OMS'},
+ "df": {"kind": "OMF", "float": val}
+ }
+
+g = -200.0
+X_fact = create_R_fact(380.0, X_ref)
+Y_fact = create_R_fact(300.0, Y_ref)
+Xv_fact = create_R_fact(-490.0, Xv_ref)
+Yv_fact = create_R_fact(150.0, Yv_ref)
+G_fact = create_R_fact(g, G_ref)
+B_fact = create_R_fact(0.8, B_ref)
+#walls_fact = create_walls_fact([[-10000.0, 0.0, 10000.0, 0.0]])
+walls_list = [[-1.0, 0.0, 401.0, 0.0],
+ [0.0, -1.0, 0.01, 401.0],
+ [400.0, -1.0, 400.01, 401.0],
+ [-1.0, 400.0, 401.0, 400.0],
+ [50.0, 200.0, 120.0, 270.0],
+ [150.0, 100.0, 200.0, 100.0],
+ [150.0, 285.0, 200.0, 200.0],
+ [230.0, 360.0, 300.0, 300.0],
+ [300.0, 100.0, 385.0, 150.0],
+ [50.0, 50.0, 100.0, 135.0]]
+walls_fact = create_walls_fact(walls_list)
+fact_list = [X_fact, Y_fact, Xv_fact, Yv_fact, G_fact, B_fact, walls_fact]
+fact_list_encoded = json.dumps(fact_list).encode('utf-8')
+
+scroll_assignment_list = [{"fact": X_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact1'}},
+ {"fact": Y_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact2'}},
+ {"fact": Xv_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact3'}},
+ {"fact": Yv_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact4'}},
+ {"fact": G_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact5'}},
+ {"fact": B_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact6'}},
+ {"fact": W_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact7'}}]
+scroll_application = {"scroll": bouncing_scroll,
+ "assignments": scroll_assignment_list}
+scroll_encoded = json.dumps(scroll_application).encode('utf-8')
+
+t1 = time.time()
+conn = http.client.HTTPConnection(HOST, port=PORT)
+conn.request("POST", "/fact/bulkadd", headers=headers, body=fact_list_encoded)
+response = conn.getresponse()
+data = response.read()
+print(response.status, response.reason)
+print(time.time() - t1)
+
+data_dict = json.loads(data.decode('utf-8'))
+
+t2 = time.time()
+conn = http.client.HTTPConnection(HOST, port=PORT)
+conn.request("POST", "/scroll/apply", headers=headers, body=scroll_encoded)
+response = conn.getresponse()
+data = response.read()
+print(response.status, response.reason)
+print(time.time() - t2)
+
+
+data_dict = json.loads(data.decode('utf-8'))
+for i in range(len(data_dict["acquiredFacts"])):
+ print(data_dict["acquiredFacts"][i])
+
+rel_fact = data_dict['acquiredFacts'][0]["df"]["arguments"]
+values = []
+def rec_vals(facts):
+ for rf in facts:
+ if rf["applicant"]["uri"] == cons_nil:
+ continue
+ elif len(rf["arguments"]) == 3:
+ rfa = rf["arguments"]
+ cvals = []
+ for ri2, rrf in enumerate(rfa):
+ cvals.extend([x["float"] for x in rrf["arguments"]])
+ values.append(cvals)
+ continue
+ else:
+ rec_vals(rf["arguments"])
+ return
+rec_vals(rel_fact)
+print("Step\tX\tY\tXv\tYv\tht\tm")
+for i, v in enumerate(values):
+ print("%d\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f" % (i, v[0], v[1], v[2], v[3], v[4], v[5]))
+
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+def get_xy(xs, ys, xv, yv, ct):
+ rx = xs + ct * xv
+ ry = ys + ct * yv + 0.5 * g * ct**2
+ return [rx, ry]
+
+plt.figure()
+for wl in walls_list:
+ plt.plot([wl[0], wl[2]], [wl[1], wl[3]], color="blue", linewidth=3)
+for i, vl in enumerate(values):
+ pvals = np.array([get_xy(vl[0], vl[1], vl[2], vl[3], cct) for cct in np.arange(0, vl[4], 0.01)])
+ plt.scatter(pvals[:, 0], pvals[:, 1], color="green", s=1)
+plt.show()
+
+
--
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